Transcript
Because of permissions issues, some material (e.g., photographs) has been removed from this chapter, though reference to it may occur in the text. The omitted content was intentionally deleted and is not needed to meet the University's requirements for this course.
CHAPTER 1 Introduction and Data Collection
USING STATISTICS: Good Tunes 1.1
BASIC CONCEPTS OF STATISTICS
1.5
TYPES OF DATA
1.2
THE GROWTH OF STATISTICS AND INFORMATION TECHNOLOGY
A.1
INTRODUCTION TO USING STATISTICAL PROGRAMS
1.3
HOW THIS TEXT IS ORGANIZED
1.4
COLLECTING DATA Identifying Sources of Data
A1.1 Using Wind Windows ows A1.2 Introduction Introduction to Microsoft Microsoft Excel A1.3 Introduction Introduction to Minitab Minitab A1.4 (CD-ROM Topic) Introduction Introduction to SPSS
LEARNING OBJECTIVES In this chapter, you learn: X 6 5 8 3 1 8 5 5 0 : N B S I
• Ho How w statistic statisticss is used in in business business • The source sourcess of data data used in business business • The types types of of data used in in business business
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
2
CHAPTER CHAPT ER ONE Introd Introducti uction on and Data Collectio Collection n
U S I N G S TAT I S T I C S Good Tunes—Part I
NOT AVAILABLE FOR ELECTRONIC VIEWING
Good Tunes, a privately held online retailer of home entertainment systems, seeks to expand its business by opening several stores. To get the financing necessary to underwrite this expansion, Good Tunes needs to apply for loans at local area banks. The managers of the firm agree to develop an electronic slide show that will explain their business and state the facts that will convince the bankers to loan Good Tunes the money it needs. You have been asked to assist in the process of preparing the slide show. What facts would you include? How would you present those facts?
E
very day you use news and information sources to gather the facts that you need to lead your life. You might listen to a weather forecast to decide what clothes to wear, and if you live in a large city, you might listen to a commuter report to learn about the best route for traveling to your job or school. Your personal likes and dislikes shape some of your decisions, too. In spite of hearing bad reviews of a motion picture that suggest you skip seeing it, you might decide to go anyhow just because you you happen to like a particular particular actor who appears appears in that film. Likewise, every day business managers have to make decisions. Although managers sometimes resort to “gut instincts” to make some decisions (this is more formally known known as unstructured decision making), they more typically make decisions that are directly influenced by hard facts. As a business student, you cannot really learn how to make unstructured decisions, as such decisions require instincts and insights that require years of experience to form. You can learn, though, the procedures and methods that will help you make better decisions that are based on hard facts. When you you begin focusing on the procedures and methods methods involved involved in the collecting, presenting, and summarizing of a set of data, or forming conclusions about that data, you have discovered statistics. In the Good Tunes scenario, you should proceed with the reasonable assumption that the bankers seek seek to make make a decision based based on the hard facts you help help present, and not on other facfactors, such as whims or personal likes or dislikes. Presenting the wrong information or the correct information in the wrong fashion could lead the bankers to make a bad business decision, which could jeopardize the future of Good Tunes. You need to know something about statistics to provide the hard facts that are necessary, and to know something about statistics, you first need to know the basic concepts of statistics.
1.1 1. 1
BASI BA SIC C CONC CONCEP EPTS TS OF OF STA STATI TIST STIC ICS S Statistics is the branch of mathematics that examines ways to process and analyze data. Statistics provides procedures to collect and transform data in ways that are useful to business decision-makers. To understand anything about statistics, you need to first understand the definition of a variable.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
1.1: Basic Concepts of Statistics
3
VARIABLES Variables are characteristics of items or individuals.
Examples of variables are your gender, your major field of study, the amount of money you have in your wallet, and the amount of time it takes you to get ready to go to school in the morning. The key aspect of the word variable is the idea that items differ and people differ. The person next to you may be male rather than female, may be majoring in a different field of study than you, almost certainly has a different amount of money in his or her wallet, and undoubtedly takes a different amount of time to get ready in the morning than you do. You should distinguish between a variable, such as gender, and its value for an individual observation (e.g., “male”). All variables should have an operational definition , a universally accepted meaning that is clear to all associated with an analysis. Without operational definitions, confusion can occur. A famous example of such confusion that illustrates the importance of operational definitions relates to the 2000 U.S. presidential election and the disputed ballots in the state of Florida (Jackie Calmes and Edward P. Foldessy, “In Election Review, Bush Wins with No Supreme Court Help,” The Wall Street Journal , November 12, 2001, A1, A14). A review of 175,010 Florida ballots that were rejected for either no presidential votes or votes for two or more candidates was conducted with the help of the National Opinion Research Center of the University of Chicago. Nine standards or operational definitions were used to evaluate these ballots. The nine standards led to different results. Three of the standards (including one pursued by Al Gore) led to margins of victory for George Bush that ranged from 225 to 493 votes. Six of the standards (including one pursued by George Bush) led to margins of victory for Al Gore that ranged from 42 to 171 votes. Now that variables have been defined, you need to understand the meaning of population, sample, parameter, and statistic.
POPULATION A population consists of all of the members of a group about which you want to draw a conclusion.
SAMPLE A sample is the portion of the population selected for analysis.
PARAMETER A parameter is a numerical measure that describes a characteristic of a population.
STATISTIC A statistic is a numerical measure that describes a characteristic of a sample.
X 6 5 8 3 1 8 5 5 0 : N B S I
Examples of populations are all the full-time students at a college, all the registered voters in New York, and all the people who went shopping at the local mall this weekend. Samples could be selected from each of the three populations mentioned above. Examples include 10 full-time students selected for a focus group, 500 registered voters in New York who were contacted via telephone for a political poll, and 30 mall shoppers who were asked to complete a customer satisfaction survey. In each case, the people in the sample represent a portion or subset of the people comprising the population. The average amount spent by all the people who went shopping at the local mall this weekend is a parameter. Information from all the shoppers in the entire population is needed to com pute this parameter. The average amount spent by the 30 shoppers completing the customer satisfaction survey is a statistic. Information from only 30 people who went to the local mall this weekend is used in calculating the statistic.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
4
CHAPTER ONE Introduction and Data Collection
Statistics, itself, is divided into two branches, both of which are applicable to managing businesses. Descriptive statistics focuses on collecting, summarizing, and presenting a set of data. Inferential statistics uses sample data to draw conclusions about a population. Descriptive statistics has its roots in the recordkeeping needs of large political and social organizations. For example, every decade since 1790, the United States has conducted a census that collects and summarizes data about its citizens. Through the years, the U.S. Census Bureau has been one of the many groups that have refined the methods of descriptive statistics. The foundation of inferential statistics is based on the mathematics of probability theory. Inferential methods use sample data to calculate statistics that provide estimates of the characteristics of the entire population. Today, applications of statistical methods can be found in different areas of business. Accounting uses statistical methods to select samples for auditing purposes and to understand the cost drivers in cost accounting. Finance uses statistical methods to choose between alternative portfolio investments and to track trends in financial measures over time. Management uses statistical methods to improve the quality of the products manufactured or the services delivered by an organization. Marketing uses statistical methods to estimate the proportion of customers who prefer one product over another and why they do, and to draw conclusions about what advertising strategy might be most useful in increasing sales of a product.
1.2
THE GROWTH OF STATISTICS AND INFORMATION TECHNOLOGY During the past century, statistics has played an important role in spurring the use of information technology and, in turn, such technology has spurred the wider use of statistics. At the beginning of the twentieth century, the expanding data-handling requirements associated with the federal census led directly to the development of tabulating machines that were the forerunners of today’s business computer systems. Statisticians such as Pearson, Fisher, Gosset, Neyman, Wald, and Tukey established the techniques of modern inferential statistics in response to the need to analyze large sets of population data that had become increasingly costly, time-consuming, and cumbersome to collect.The development of early computer systems permitted others to develop computer programs to ease the calculational and data-processing burdens imposed by those techniques. These first programs, in turn, allowed greater use of statistical methods by business decision-makers, and this greater use, as well as more recent advances in information technology, have com pleted the cycle by spurring the development of even more sophisticated statistical methods. Today, when you hear of retailers investing in a “customer-relationship management system” or a packaged goods producer engaging in “data mining” to uncover consumer preferences, you should realize that statistical techniques form the foundations of such cutting-edge applications of information technology. Even though cutting-edge applications might require custom programming, for many years businesses have had access to statistical packages , such as Minitab and SPSS, that are standardized sets of programs that help managers use a wide range of statistical techniques by automating the data processing and calculations these techniques require. Whereas such packages were once available only in corporate computing centers, the increasing power and connectivity of personal computers have brought the statistical power of these packages to the desktop, where they have joined such familiar tools as word processing, worksheet, and Web browser programs. The leasing and training costs associated with statistical packages have led many to consider using some of the graphical and statistical functions of Microsoft Excel. However, you need to be aware of concerns that many statisticians have about the accuracy and completeness of the statistical results that Excel produces. Unfortunately, some investigators have determined that certain Microsoft Excel statistical capabilities contain flaws that can lead to invalid results, especially when the data sets used are very large or have unusual statistical properties (see reference 3). Clearly, when you use Microsoft Excel, you must be careful about the data and the analysis you are undertaking. Whether this complication outweighs the benefits of Excel’s attractive features is still an unanswered question in business today.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
1.3: How This Text Is Organized
1.3
5
HOW THIS TEXT IS ORGANIZED The primary goal of this text is helping you learn to understand how the methods of statistics can be used in decision-making processes. For business students, this understanding includes the following objectives: • • • •
To properly present and describe business data and information To draw conclusions about large populations based solely on information collected from samples To make reliable forecasts about business trends To improve business processes
This text uses these four objectives listed above as its organizing principle. Figure 1.1 shows how each chapter relates to these objectives. You will explore the methods involved in the collection, presentation, and description of information in the remaining portion of this chapter and
Rational Decision Making
Presenting and Describing Information
Drawing Conclusions about Populations, Based Only on Sample Information
Improving Processes
Making Reliable Forecasts of Variables of Interest
Introduction and Data Collection (Chapter 1)
Basic Probability (Chapter 4)
Statistical Applications in Quality and Productivity Management (Chapter 14)
Simple Linear Regression (Chapter 12)
Presenting Data in Tables and Charts (Chapter 2)
Some Important Discrete Probability Distributions (Chapter 5)
Numerical Descriptive Measures (Chapter 3)
The Normal Distribution (Chapter 6)
Multiple Regression (Chapter 13)
Sampling Distributions (Chapter 7)
X 6 5 8 3 1 8 5 5 0 : N B S I
Confidence Interval Estimation (Chapter 8)
Fundamentals of Hypothesis Testing (Chapters 9–11)
FIGURE 1.1 Structure Chart for This Text Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
6
CHAPTER ONE Introduction and Data Collection
Chapters 2 and 3. In Chapters 4 through 7 you will learn about the basic concepts of probability, and the binomial, normal, and other distributions to better understand, in Chapters 8 through 11, how you can draw conclusions about large populations based solely on information from samples. In Chapters 12 and 13 you will focus on regression analysis that can be used to make forecasts. In Chapter 14 you will learn methods for improving business processes. Because learning in context enhances comprehension, each chapter begins with a “Using Statistics” scenario, such as the “Good Tunes—Part I” on page 2, that identifies a business problem in which statistics can be applied to change data into the useful information required for a rational decision. Questions raised in the scenarios lead to answers in the form of statistical methods presented in subsequent sections of the text. By thinking about these questions, you will gain an appreciation of how business managers are using statistics today to solve problems and improve the quality of their products and services. For the “Good Tunes—Part I” scenario, selecting what to present is just as important as selecting the proper method for presentation and summarization. In this case, presumably the bankers themselves would demand some of the data, the “financials” of the business. But what other data could you collect and present that would help win the approval of the loans? (See “Good Tunes—Part II” below.) Of course, having presented your data, you would hope that the bankers would make the right inferences. That is, you would hope that the bankers were knowledgeable about the appropriate statistical methods that assist in the loan-making decision!
U S I N G S TAT I S T I C S Good Tunes—Part II The owners of Good Tunes have decided to supplement the financial data in their loan application with data concerning customer perceptions about Good Tunes. To help assess these perceptions, Good Tunes has been asking its customers to complete and promptly return a customer satisfaction survey that is included in every order. The survey includes the following questions:
How many days did it take from the time you ordered your merchandise to the time you received it? ________ How much money (in U.S. dollars) do you expect to spend on stereo and consumer electronics equipment in the next twelve months? ________ How do you rate the overall service provided by Good Tunes with respect to your recent purchase? Much better than expected Better than expected About as expected
Worse than expected Much worse than expected
□ □
How do you rate the quality of the items you recently purchased from Good Tunes? Much better than expected Better than expected About as expected
□ □ □
□ □ □
Worse than expected Much worse than expected
□ □
Are you likely to buy additional merchandise through Good Tunes in the next twelve months? Yes □ No □
You have been asked to review the survey. What type of data does the survey seek to collect? What type of information can be generated from the data of the completed survey? How can Good Tunes use that information to improve the perceived quality of the service and merchandise? How can Good Tunes use that information to increase its chance of getting a loan approval? What other questions would you suggest to include in the survey?
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
1.4: Collecting Data
1.4
7
COLLECTING DATA Managing a business effectively requires collecting the appropriate data. In most instances, the data are measurements acquired from items in a sample. The samples are chosen from populations in such a manner that the sample is as representative of the population as possible. The most common technique to ensure proper representation is to use a random sample. (See Chapter 7 for a detailed discussion of sampling techniques.) Many different types of circumstances require the collection of data: • • • • •
A marketi ng res earch analys t needs to as sess the effectiven ess of a n ew televis ion advertisement. A pharmaceutical manufacturer needs to determine whether a new drug is more effective than those currently in use. An operations manager wants to monitor a manufacturing process to find out whether the quality of a product is conforming to company standards. An auditor wants to review the financial transactions of a company in order to determine whether or not the company is in compliance with generally accepted accounting principles. A potential investor wants to determine which firms within which industries are likely to have accelerated growth in a period of economic recovery.
Identifying Sources of Data Identifying the most appropriate source of data is a critical aspect of statistical analysis. If biases, ambiguities, or other types of errors flaw the data being collected, even the most sophisticated statistical methods will not produce accurate information. Four important sources of data are: • • • •
X 6 5 8 3 1 8 5 5 0 : N B S I
Data distributed by an organization or an individual A designed experiment A survey An observational study
Data sources are classified as being either primary sources or secondary sources . When the data collector is the one using the data for analysis, the source is primary. When one organization or individual has compiled the data that are used by another organization or individual, the source is secondary. Organizations and individuals that collect and publish data typically use that data as a primary source and then let others use it as a secondary source. For example, the United States federal government collects and distributes data in this way for both public and private pur poses. The Bureau of Labor Statistics collects data on employment as well as distributing the monthly Consumer Price Index . The Census Bureau oversees a variety of ongoing surveys regarding population, housing, and manufacturing and undertakes special studies on topics such as crime, travel, and health care. Market research firms and trade associations also distribute data pertaining to specific industries or markets. Investment services such as Mergent’s provide financial data on a company-by-company basis. Syndicated services such as A. C. Nielsen provide clients with data enabling the comparison of client products with those of their competitors. Daily news papers are f illed with numerical information regarding stock prices, weather conditions, and sports statistics. As listed above, conducting an experiment is another important data collection source. For example, to test the effectiveness of laundry detergent, an experimenter determines which brands in the study are more effective in cleaning soiled clothes by actually washing dirty laundry instead of asking customers which brand they believe to be more effective. Proper experimental designs are usually the subject matter of more advanced texts, because they often involve sophisticated statistical procedures. However, some fundamental experimental design concepts will be considered in Chapter 10.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
8
CHAPTER ONE Introduction and Data Collection
Conducting a survey is a third important data source. Here the people being surveyed are asked questions about their beliefs, attitudes, behaviors, and other characteristics. Responses are then edited, coded, and tabulated for analysis. Conducting an observational study is the fourth important data source. In such a study, a researcher observes the behavior directly, usually in its natural setting. Observational studies take many forms in business. One example is the focus group, a market research tool that is used for eliciting unstructured responses to open-ended questions. In a focus group, a moderator leads the discussion, and all the participants respond to the questions asked. Other, more structured types of studies involve group dynamics and consensus building and use various organizational behavior tools such as brainstorming, the Delphi technique, and the nominalgroup method. Observational study techniques are also used in situations in which enhancing teamwork, or improving the quality of products and service are management goals.
1.5
TYPES OF DATA Data are the observed values of variables, for example, the responses to a survey. Statisticians develop surveys to deal with a variety of different variables. As illustrated in Figure 1.2, there are two types of variables—categorical and numerical.
FIGURE 1.2 Types of Variables
Data Type
Question Types
Responses
Do you currently own any stocks or bonds? Yes
Categorical
No
Discrete
To how many magazines do you currently subscribe?
Number
Continuous
How tall are you?
Inches
Numerical
Categorical variables yield categorical responses, such as yes or no answers. An example is the response to the question “Do you currently own any stocks or bonds?” because it is limited to a simple yes or no answer. Another example is the response to the question on the GoodTunes survey (presented on page 6), “Are you likely to buy additional merchandise through Good Tunes in the next 12 months?” Categorical variables can also yield more than two possible responses. For example, “Which day of the week are you most likely to eat dinner in a restaurant?” Numerical variables yield numerical responses such as your height in inches. Other exam ples are how much money you expect to spend on stereo equipment in the next 12 months (from the Good Tunes customer satisfaction survey) or the response to the question “To how many magazines do you currently subscribe?” There are two types of numerical variables: discrete and continuous. Discrete variables produce numerical responses that arise from a counting process. “The number of magazines subscribed to” is an example of a discrete numerical variable, because the response is one of a finite number of integers. You subscribe to zero, one, two, and so on, magazines. Continuous variables produce numerical responses that arise from a measuring process. Your height is an example of a continuous numerical variable, because the response takes on any value within a continuum or interval, depending on the precision of the measuring instru7 58 ment. For example, your height may be 67 inches, 67 41 inches, 6732 inches, or 67 250 inches, depending on the precision of the available instruments. No two persons are exactly the same height and the more precise the measuring device used, the greater the likelihood of detecting differences between their heights. However, most measuring devices are not sophisticated enough to detect small differences. Hence, tied observations are often found in experimental or survey data even though the variable is truly continuous, and theoretically all values of a continuous variable are different.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
Summary
9
PROBLEMS FOR SECTION 1.5 Learning the Basics 1.1 Three different beverages are sold at a fast-food restaurant—soft drinks, tea, and coffee. Explain why the type of beverage sold is an example of a categorical variable.
1.2 Soft drinks are sold in three sizes in a fast-food restaurant—small, medium, and large. Explain why the size of the soft drink is a categorical variable.
1.3 Suppose that you measure the time it takes to download an MP3 file from the Internet. a. Explain why the download time is a numerical variable. b. Is the variable discrete or continuous?
Applying the Concepts SELF
1.4 For each of the following variables, deter-
mine whether the variable is categorical or numerical. If the variable is numerical, determine whether the variable is discrete or continuous. a. Number of telephones per household b. Length (in minutes) of the longest long-distance call made per month c. Whether there is a telephone line connected to a com puter modem in the household d. Whether there is a fax machine in the household Test
PH Grade
1.5 The following information is collected from
students upon exiting the campus bookstore during the first week of classes: a. Amount of time spent shopping in the bookstore b. Number of textbooks purchased c. Academic major d. Gender Classify each of these variables as categorical or numerical. If the variable is numerical, determine whether the variable is discrete or continuous. ASSIST
PH Grade
1.6 For each of the following variables, deter-
mine whether the variable is categorical or numerical. If the variable is numerical, determine whether the variable is discrete or continuous. a. Name of Internet provider b. Amount of time spent surfing the Internet per week c. Number of e-mails received in a week d. Number of online purchases made in a month ASSIST
1.7 For each of the following variables, determine whether the variable is categorical or numerical. If the variable is
X 6 5 8 3 1 8 5 5 0 : N B S I
numerical, determine whether the variable is discrete or continuous. a. Amount of money spent on clothing in the last month b. Favorite department store c. Most likely time period during which shopping for clothing takes place (weekday, weeknight, or weekend) d. Number of pairs of winter gloves owned
1.8 Suppose the following information is collected from Robert Keeler on his application for a home mortgage loan at the Metro County Savings and Loan Association: a. Monthly Payments: $1,427 b. Number of Jobs in Past 10 Years: 1 c. Annual Family Salary Income: $86,000 d. Marital Status: Married Classify each of the responses by type of data.
1.9 One of the variables most often included in sur veys is income. Sometimes the question is phrased “What is your income (in thousands of dollars)?” In other surveys, the respondent is asked to “Place an X in the circle corresponding to your income level” and given a number of ranges to choose from. a. In the first format, explain why income might be considered either discrete or continuous. b. Which of these two formats would you prefer to use if you were conducting a survey? Why? c. Which of these two formats would likely bring you a greater rate of response? Why?
1.10 If two students score a 90 on the same examination, what arguments could be used to show that the underlying variable—test score—is continuous?
1.11 The director of market research at a large department store chain wanted to conduct a survey throughout a metr op olita n are a to d eter mine the amou nt of t ime working women spend shopping for clothing in a typical month. a. Describe both the population and the sample of interest, and indicate the type of data the director might wish to collect. b. Develop a first draft of the questionnaire needed in (a) by writing a series of three categorical questions and three numerical questions that you feel would be appro priate for this survey.
SUMMARY In this chapter you have studied data collection and the various types of data used in business. In the “Using Statistics” scenario you were asked to review the customer
survey used by the Good Tunes Company (see page 6). The first two questions shown will produce numerical data and the last three will produce categorical data. The
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
10
CHAPTER ONE Introduction and Data Collection
responses to the first question (number of days) are discrete, and the responses to the second question (amount of money spent) are continuous. After the data have been collected, they must be organized and prepared in order to
KEY
make various analyses. In the next two chapters, tables and charts and a variety of descriptive numerical measures that are useful for data analysis are developed.
TERMS
categorical variables 8 continuous variables 8 data 8 descriptive statistics 4 discrete variables 8 focus group 8
CHAPTER
inferential statistics 4 numerical variables 8 operational definition 3 parameter 3 population 3 primary sources 7
REVIEW
sample 3 secondary sources 7 statistic 3 statistics 2 statistical packages 4 variables 3
PROBLEMS
Checking Your Understanding
1.22 The Gallup organization releases the results of recent
1.12 What is the difference between a sample and a popu-
ential statistics?
polls at its Web site www.gallup.com . Go to this site and click on an article of interest to you in the “Top Stories” section. a. Give an example of a categorical variable found in the article. b. Give an example of a numerical variable found in the article. c. Is the variable you selected in (b) discrete or continuous?
1.15 What is the difference between a categorical and a
1.23 The U.S. Census Bureau www.census.gov site con-
numerical variable?
tains survey information on people, business, geography, and other topics. Go to the site and click on Housing in the “People” section. Then click on American Housing Survey. a. Briefly describe the American Housing Survey. b. Give an example of a categorical variable found in this survey. c. Give an example of a numerical variable found in this survey. d. Is the variable you selected in (c) discrete or continuous?
lation?
1.13 What is the difference between a statistic and a parameter?
1.14 What is the difference between descriptive and infer-
1.16 What is the difference between a discrete and a continuous variable?
1.17 What is an operational definition and why is it so important?
Applying the Concepts 1.18 The Data and Story Library lib.stat.cmu.edu/DASL is an online library of data files and stories that illustrate the use of basic statistical methods. The stories are classified by method and by topic. Go to this site and click on List all topics . Pick a story and summarize how statistics are used in the story.
1.19 Go to the off icial Microsoft Excel Web site www.microsoft.com/office/excel. Explain how you think Microsoft Excel could be useful in the field of statistics.
1.20 Go to the official Minitab Web site www.minitab.com . Explain how you think Minitab could be useful in the field of statistics.
1.21 Go to the official SPSS Web site www.spss.com . Explain how you think SPSS could be useful in the f ield of statistics.
1.24 On the U.S. Census Bureau www.census. gov site, click on Survey of Business Owners in the “Business” section and read the description of The Survey of Business Owners and Self-Employed Persons (SBO). Click on SBO-1 in the “Forms and Instructions” section to view the actual survey form used. a. Give an example of a categorical random variable found in this survey. b. Give an example of a numerical random variable found in this survey. c. Is the variable you selected in (b) discrete or continuous?
1.25 In a report based on U.S. Transportation Department statistics, the budget carrier JetBlue was number 1 in quality among all U.S. airlines in 2003. JetBlue had the second best on-time performance, arriving on time 86% of the
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
Introduction to the Web Cases
time. Also, JetBlue customers filed fewer complaints than all other airlines but one (“JetBlue ranked No. 1 Airline, Report Says,” USAToday.com, April 5, 2004). a. Which of the four types of data sources listed in Section 1.4 on page 7 do you think were used in this study? b. Name a categorical variable discussed in this article. c. Name a numerical variable discussed in this article.
11
a. Describe the population for the Goldman Sachs survey. b. Describe the population for the Cyber Dialogue survey. c. Is a response to the question “Why did you quit online banking?” categorical or numerical? d. Twenty-seven percent of respondents indicated that online banking was too complicated or too time-consuming. Is this a parameter or a statistic?
1.26 According to a Goldman Sachs survey, only about 4% of U.S. households bank online. A survey by Cyber Dialogue investigated reasons people quit online banking after trying it. A partial listing of the results of the Cyber Dialogue survey are given below (“USA Snapshots,” USA Today, February 21, 2000, A1). Why Did You Quit Online Banking?
Too complicated or time-consuming
27%
Unhappy with customer service
25%
No need/not interested
20%
Concerns about security or fraud
11%
Too costly
11%
Concerns about privacy
5%
1.27 A manufacturer of cat food was planning to survey households in the United States to determine purchasing habits of cat owners. Among the questions to be included are those that relate to 1. where cat food is primarily purchased. 2. whether dry or moist cat food is purchased. 3. the number of cats living in the household. 4. whether or not the cat is pedigreed. a. Describe the population. b. For each of the four items listed, indicate whether the variable is categorical or numerical. If numerical, is it discrete or continuous? c. Develop five categorical questions for the survey. d. Develop five numerical questions for the survey.
INTRODUCTION TO THE WEB CASES LEARNING FROM THE WEB CASES IN THIS TEXT
X 6 5 8 3 1 8 5 5 0 : N B S I
People use statistical techniques to help communicate and present important information to others both inside and outside their businesses. And every day, people misuse these techniques: • A sales manager working with an “easy-to-use” charting program chooses an inappropriate chart that obscures data relationships. • The editor of an annual report presents a chart of revenues with an abridged Y -axis that creates the false impression of greatly rising revenues. • An analyst generates meaningless statistics about a set of categorical data using analyses designed for numerical data. Although much of the misuse of statistics is unintentional, you need to be able to identify all such misuses in order to be an infor med manager. The primar y goal of the Web Cases throughout this text is to help you develop this type of skill. Web Cases ask you to visit the Web sites that are related to the companies and issues raised in the “Using Statistics” scenario that starts each chapter or a Web page that supports the continuing story of the Springville Herald , a small-city daily newspaper. You review internal documents as well as
publicly stated claims, seeking to identify and correct the misuses of statistics. Unlike a traditional text case study, but much like real-world situations, not all of the information you encounter will be relevant to your task, and you may occasionally discover conflicting information that you need to resolve before continuing with the case. To assist your learning, the Web Case for each chapter begins with the learning objective and a synopsis of the scenario under consideration. You will be directed to a specific Web site or Web page and given a set of questions that will guide your exploration. If you prefer, you can also explore the Web pages for the cases by linking to the Springville Chamber of Commerce page www.prenhall.com/ Springville/SpringvilleCC.htm . Complementing the Web Case in most chapters is a traditional case study exercise in which you are asked to apply your knowledge of statistics to a problem being faced by the management of the Springville Herald . To illustrate how to use a Web Case, link to the Web site for Good Tunes www.prenhall.com/Springville/ Good_Tunes.htm , the online retailer mentioned in the “Using Statistics” scenarios for this chapter. Recall that the privately held Good Tunes is seeking financing to expand its business by opening retail locations. Since it is in management’s interest to show that Good Tunes is a
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
12
CHAPTER ONE Introduction and Data Collection
thriving business, it is not too surprising to discover the impression that unit sales data are being presented. If the “our best sales year ever” claim in the “Good Times at data are unit sales, does such data best support the claim GoodTunes” entry at the top of their home page. being made—or would something else, such as dollar The claim is also a hyperlink, so click on “our best volumes—be a better indicator of sales at Good Tunes? sales year ever” to display the page that supports the claim. Then there are those curious chart labels. “Latest How would you support such a claim? With a table of twelve months” is ambiguous—it could include months numbers? A chart? Remarks attributed to a knowledgeable from the current year as well as months from one year ago source? Good Tunes has used a chart to present “two years and therefore may not be an equivalent time period to “two ago” and “latest twelve month’s” sales data by category. years ago.” Since the business was established in 1997, and Are there any problems with the choices made on this Web the claim being made is “best sales year ever,” why hasn’t page? Absolutely! management included sales figures for every year? First, note that there are no scales for the symbols Is Good Tunes management hiding something or are used, so it is impossible to know what the actual sales volthey just unaware of the proper use of statistics? Either umes are. In fact, as you will learn in section 2.6, charts way, they have failed to properly communicate a vital that incorporate symbols in this way are considered examaspect of their “story.” ples of chartjunk and would never be used by people seekIn subsequent Web Cases, you are asked to provide ing to properly use graphs. this type of analysis, using the open-ended questions preThis important point aside, another question that arises sented in this text as guidance. Not all the cases are as is whether the sales data represent the number of units sold straightforward as this sample and some cases include or something else. The use of the symbols creates the perfectly appropriate applications of statistics.
REFERENCES 1. Kendall, M. G., and R. L. Plackett, eds., Studies in the History of Statistics and Probability , vol. 2 (London: Charles W. Griffin, 1977). 2. Kirk, R. E., ed., Statistical Issues: A Reader for the Behavioral Sciences (Monterey, CA: Brooks/Cole, 1972). 3. McCullough, B. D., and B. Wilson, “On the accuracy of statistical procedures in Microsoft Excel 97,” Computational Statistics and Data Analysis , 31 (1999), 27–37. 4. Microsoft Excel 2003 (Redmond, WA: Microsoft Corporation , 2002).
Appendix 1
5. Minitab Release 14 (State College, PA: Minitab, Inc., 2004). 6. Pearson, E. S., ed., The History of Statistics in the Seventeenth and Eighteenth Centuries (New York: Macmillan, 1978). 7. Pearson, E. S., and M. G. Kendall, eds., Studies in the History of Statistics and Probability (Darien, CT: Hafner, 1970). 8. SPSS® Base 12.0 Brief Guide (Upper Saddle River, NJ: Prentice Hall, 2003).
Introduction to Using
Statistical Programs ABOUT THIS APPENDIX Section A1.1 Read this section if you are unfamiliar with the basics of Microsoft Windows operations that are required in order to use Microsoft Excel, Minitab, or SPSS effectively.
Section A1.2 Read this section only if you plan to use Microsoft Excel with this text. Section A1.3 Read this section only if you are using Minitab with this text. Section A1.4 Read this CD-ROM section only if you are using SPSS with this text.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
Appendix
Note: Throughout this appendix and all other appendices in this text, the symbol is used to represent a sequence of menu selections. For example, the instruction “select File Open ” means to first select the File menu choice and then select the Open choice from the submenu that appears.
A1.1 USING WINDOWS Using the Mouse In Microsoft Windows, you frequently use a mouse or other pointing device to make choices by pointing to an onscreen object and pressing a mouse button. By convention, Windows expects pointing devices to contain two buttons, one designated as the primary button, the other as the secondary button. You can move your mouse and press and release the mouse buttons in the following ways: Click or Select: Move the mouse over an object and press the primary button. Drag: Move the mouse over an object. Then while pressing and holding down the primary button, move the mouse pointer somewhere else on the screen and release the primary button. Dragging either moves objects to another part of the screen or allows you to select multiple items. Double-click: Move the mouse over an object and click the primary button twice in rapid succession. Right-click: Move the mouse over an object and click the secondary button.
By default, Microsoft Windows defines the left mouse button as the primary button and the right button as the secondary button (this gives rise to the phrase “right-click”), but you can swap the definitions by selecting the Windows Mouse Control Panel icon.
Opening Programs You can choose one of two ways to directly open a program such as Microsoft Excel, Minitab, or SPSS for use. These ways are: •
• X 6 5 8 3 1 8 5 5 0 : N B S I
Program icon click: Double-click the Windows desktop icon representing the program (in some Windows versions, you may need only to single click the icon). Start Menu selection: Press the Windows key (or click the onscreen Start button) and select the Programs or All Programs choice. From the menu list that appears, select the entry for the program. If the program is listed on a submenu, you will have to first select the submenu, and then select the program.
13
Experienced Microsoft Windows users may know other ways to open a program. You can, of course, use these other ways if you prefer.
Program Windows Microsoft Windows gets its name because every time you open a program, an onscreen rectangular frame or “window” opens as well. Inside this window, you interact with the program and many interactions lead to the opening of additional windows into which you make entries and selections. The opening window of most programs contains these common elements: A title bar at the top of the window that identifies the program and any file in use. Resize buttons on the right side of the title bar area that affect the displayed size of the window. A Close program button on the right margin of the title bar that allows you to quickly end your use of a program. A menu bar, a horizontal list of words below the title bar that contains command choices on one or more menus. One or more tool bars that contain buttons that are command shortcuts. Figure A1.1 shows these common elements for the opening windows in Microsoft Excel 2003, Minitab Release 14, and SPSS Student Version 12. Note the windows for these programs additionally have a worksheet area composed of rows and columns that you use for data entry.
Dialog Boxes Many entries and selections you make as you use a program trigger the display of additional windows known as dialog boxes. The Microsoft Excel 2003 dialog boxes to open or print a file (see Figure A1.2) contain the following elements commonly found in all dialog boxes: Question mark help button: Clicking this button allows you to then click on an element of the dialog box to display a help message about that element. Drop-down list box: Displays a list of choices when you click the drop-down button that appears at the right edge of the box. List box: Displays a list of choices. Sometimes includes scroll buttons or a slider if the list of choices is larger than the size the box can display. Text box: Provides a space into which you can type an entry. These boxes are sometimes combined with either a drop-down list or spinner buttons (seen in the
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
14
CHAPTER ONE Introduction and Data Collection
Close program buttons Resize buttons
Menu bars Tool bars
Title bars
Worksheet areas
FIGURE A1.1 Program Windows for Microsoft Excel, Minitab, and SPSS
Question mark help buttons Drop-down list boxes
List box
Text boxes
Check boxes
Icons Option buttons I S B N : 0 5 5 8 1 3 8 5 6 X
Command buttons
FIGURE A1.2 Common Dialog Box Elements
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
Appendix
Pages From box in Figure A1.2) that provide alternative ways to specifying an entry. Check box: Provides a set of choices in which you can make zero, one, or more than one choice (compare with option buttons). Icons: Allows you direct access to other places in your Windows system where files may be stored. Option buttons: Provides a set of mutually exclusive choices in which only one choice can be selected at a time. Command buttons: Causes the program to take some action that usually closes the current dialog box and triggers the display of an additional dialog box. An OK button causes the program to take an action using the current values and settings of the dialog box. A Cancel button closes a dialog box and cancels the operation associated with the dialog box.
A1.2 INTRODUCTION TO MICROSOFT EXCEL Microsoft Excel Overview Microsoft Excel is the electronic worksheet program of Microsoft Office. Although not a specialized statistical program, Excel contains basic statistical functions and includes Data Analysis Tool Pak procedures that you can use to perform selected advanced statistical methods. You can also install the Prentice Hall PHStat2 add-in (included with the CD-ROM packaged with this text) to extend and enhance the Data Analysis Tool Pak that Microsoft Excel contains. (You do not need to use PHStat2 in order to use Microsoft Excel with this text, although using PHStat2 will simplify using Excel for statistical analysis.) In Microsoft Excel, you create or open and save files that are called workbooks . Workbooks are collections of worksheets and related items such as charts that contain the original data as well as the calculations and results associated with one or more analyses. Because of its widespread distribution, Microsoft Excel is a convenient program to use, but some statisticians express concern about its lack of fully reliable and accurate results for some statistical procedures. Although Microsoft has improved many statistical functions starting with Excel 2003, you should be cautious about using Microsoft Excel to perform analyses on data other than the data used in this text. (If you plan to install PHStat2, make sure to first read Appendix F and any PHStat2 read-me file that may appear on the included CD-ROM.) X 6 5 8 3 1 8 5 5 0 : N B S I
Using Microsoft Excel Worksheets In Microsoft Excel, you enter data into worksheets that are organized as lettered columns and numbered rows.Typically,
15
you enter the data for each variable in a separate column, using the row 1 cell for a variable label and each subsequent row for a single observation. You should follow the good practice of entering only one set of data per worksheet. To refer to a specific entry, or cell, you use a Sheetname!ColumnRow notation. For example, Data!A2 refers to the cell in column A and row 2 in the Data worksheet. To refer to a specific group or range of cells, you use a Sheetname!Upperleftcell:Lowerrightcell notation. For example, Data!A2:B11 refers to the 20 cells that are in rows 2 though 11 in columns A and B of the Data worksheet. Each Microsoft Excel worksheet has its own name. Automatically, Microsoft Excel names worksheets in the form of Sheet1, Sheet2, and so on. You should rename your worksheets, giving them more self-descriptive names, by double-clicking the sheet tabs that appear at the bottom of each sheet, typing a new name, and pressing the Enter key.
Using Formulas in Excel Worksheets Formulas are worksheet cell entries that perform a calculation or some other task. You enter formulas by typing the equal sign symbol (=) followed by some combination of mathematical or other data-processing operations. For simple formulas, you use the symbols +, −, *, /, and ^ for the operations addition, subtraction, multiplication, division, and exponentiation (a number raised to a power), respectively. For example, the formula =Data!B2 + Data!B3 + Data!B4 + Data!B5 adds the contents of the cells B2, B3, B4, and B5 of the Data worksheet and dis plays the sum as the value in the cell containing the formula. You can also use Microsoft Excel functions in formulas to simplify formulas. For example, the formula =SUM(Data!B2:B5) that uses the Excel SUM() function is a shorter equivalent to the formula of the previous sentence. You can also use cell or cell range references that do not contain the Sheetname ! part, such as B2 or B2:B5. Such references always refer to the worksheet in which the formula has been entered. Formulas allow you to create generalized solutions and give Excel its distinctive ability to automatically recalculate results when you change the values of the supporting data. Typically, when you use a worksheet, you see only the results of any formulas entered, not the formulas themselves. However, for your reference, many illustrations of Microsoft Excel worksheets in this text also show the underlying formulas adjacent to the results they produce. When using Excel, you can select Tools Options and in the View tab of the Options dialog box that appears, select the Formulas check box, and click the OK button to see onscreen the formulas themselves and not their results. To restore the original view, uncheck the Formulas check box.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
16
CHAPTER ONE Introduction and Data Collection
Using the Microsoft Excel Chart Wizard You use the Microsoft Excel Chart Wizard to generate a wide variety of charts. The Chart Wizard is one of several Microsoft Office wizards, sets of linked dialog boxes that guide you, step-by-step, through the task of creating something. To use the Chart Wizard, you first select Insert Chart. Then you make selections and enter information about the properties of the chart as you step through the dialog boxes by clicking a Next button. Clicking the Finish button in the last dialog box ends the wizard and creates the chart. At any point, you can cancel the operation of the wizard by clicking a Cancel button or move to a previous dialog box by clicking Back. The Chart Wizards of the various versions of Microsoft Excel differ slightly. For Microsoft Excel 2003, the four-step wizard (see Figure A1.3 below) requires you to do the following: Step 1: Choose the chart type. Step 2: Enter the workbook locations of the source data for the values to be plotted and the source data for chart labeling information (if any). Step 3: Specify the formatting and labeling options for the chart. (See further comments at right.)
Step 4: Choose the workbook location of the chart. You will always create a better-scaled chart if you choose the “as new sheet” instead of the “as object in (a worksheet)” option.
You can change these settings after the chart has been produced by right-clicking on the chart and making the appro priate selection from the shortcut menu that appears. For example, to reconsider the settings associated with the Step 3 dialog box, you would select Chart Options from the shortcut menu. The automatic settings in the Step 3 dialog box create imperfectly designed charts. When you are using the Chart Wizard to generate charts for problems and examples from this text, in the dialog box you should select the tabs listed below (see Figure A1.4) and apply the following instructions (if a tab does not appear in the Step 3 dialog box for a particular chart type, ignore the instruction for the tab): • •
•
Select the Titles tab and enter a title and axis labels, if appropriate. Select the Axes tab and then select both the (X) axis and (Y) axis check boxes. Also select the Automatic option button under the (X) axis check box. Select the Gridlines tab and deselect (uncheck) all the choices under the (X) axis heading and under the (Y) axis heading.
I S B N : 0 5 5 8 1 3 8 5 6 X
FIGURE A1.3 Microsoft Excel Chart Wizard Dialog Boxes
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
Appendix
17
FIGURE A1.4 Chart Wizard Step 3 Dialog Box Tabs • •
Select the Legend tab and deselect (uncheck) the Show legend check box. Select the Data Labels tab and in the Data labels group, select the None option button.
Opening and Saving Workbooks You open workbooks to use data and results that have been created by you or others at an earlier time. To open a Microsoft Excel workbook, f irst select File Open. In the Open dialog box that appears (see Figure A1.5), you select the file to be opened and then click the OK button. If you cannot find your file, you may need to do one or more of the following: • • •
Use the scroll bars or the slider, if present, to scroll through the entire list of files. Select the correct folder from the Look in drop-down list at the top of the dialog box. Change the Files of type value from the drop-down list at the bottom of the dialog box. You should select Text Files from the list to see any text files; to list every file in the folder, select All Files .
FIGURE A1.5 Microsoft Excel Open Dialog Box
X 6 5 8 3 1 8 5 5 0 : N B S I
To save a workbook, select File Save As to display the Save As dialog box, which is similar to the Open dialog box. Enter (or edit) the name of the file in the File name box and click the OK button. If applicable, you can also do the following: •
Change to another folder by selecting that folder from the Save in drop-down list.
•
Change the Save as type value to something other than the default choice, Microsoft Excel Workbook . “Text (Tab delimited) ” or “CSV (Comma delimited) ” are two file types sometimes used to share Excel data with other programs.
After saving your work, you should consider saving your file a second time, using a different name, in order to create a backup copy of your work. Files opened from nonwritable disks, such as the CD-ROM packaged with this text, cannot be saved to their original folders.
Printing Workbooks To quickly print Excel worksheets you can select File Print and then click the OK button in the Print dialog box. However, except for the simplest worksheets, you will probably want to preview the printed output and make any necessary adjustments before actually printing. To do this, select the worksheet to be printed and then select File Print Preview. If the preview contains formatting errors, click the Close button, make the changes necessary, and reselect File Print Preview. When you are satisfied with the results, click the Print button in the Print Preview window and then click the OK button in the Print dialog box. The Print dialog box (see Figure A1.2 on page 14) contains settings to select the printer to be used, what parts of the workbook to print (the active worksheet is the default), and the number of copies to produce (1 is the default). If you need to change these settings, change them before clicking the OK button. After printing, you should verify the contents of your printout. Most printing failures will trigger the display of an error message that you can use to figure out the source of the failure. You can customize your printouts by selecting File Page Setup (or clicking the Setup button in the Print Preview window) and making the appropriate entries in the Page Setup dialog box (not shown) before printing your worksheets.
A1.3 INTRODUCTION TO MINITAB Minitab Overview Minitab is a statistical program that initially evolved from efforts at the Pennsylvania State University to improve the teaching of statistics. Today, while still used in many schools, Minitab has become a commercial product that is used in large corporations worldwide including Ford Motor Company, 3M, and GE.
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
18
CHAPTER ONE Introduction and Data Collection
In Minitab, you create and open projects to store all of your data and results. A session, or log of activities, a Project Manager that summarizes the project contents, and any worksheets or graphs used are the components that form a project. Project components are displayed in separate windows inside the Minitab application window. By default, you will see only the session and one worksheet window when you begin a new project in Minitab. (You can bring any window to the front by selecting the window in the Minitab Windows menu.) You can open and save an entire project or, as is done in this text, open and save worksheets. Minitab’s accuracy, availability for many different types of computer systems, and commercial acceptance makes this program a great tool for learning statistics.
Using Minitab Worksheets You enter data in a Minitab worksheet so that each variable is assigned to a column. Minitab worksheets are organized as numbered rows and columns numbered in the form Cn in which C1 is the first column.You enter variable labels in a special unnumbered row that precedes row 1. Unlike worksheets in programs such as Microsoft Excel, Minitab worksheets do not accept formulas and do not automatically recalculate themselves when you change the values of the supporting data. By default, Minitab names open worksheets serially in the form of Worksheet1, Worksheet2, and so on. Better names are ones that reflect the content of the worksheets, such as Funds for a worksheet that contains mutual funds data. To give a sheet a descriptive name, open the Project Manager window, right-click the icon for the worksheet, and select Rename from the shortcut menu and type in the new name.
Opening and Saving Worksheets and Other Components You open worksheets to use data that have been created by you or others at an earlier time. To open a Minitab worksheet, first select File Open Worksheet. In the Open Worksheet dialog box that appears (see Figure A1.6), you select the file to be opened and then click the OK button. If you cannot find your file, you may need to do one or more of the following: • • •
Use the scroll bars or the slider, if present, to scroll through the entire list of files. Select the correct folder from the Look in drop-down list at the top of the dialog box. Change the Files of type value from the drop-down list at the bottom of the dialog box. You should select Text Files from the list to see any text files; to list every file in the folder, select All Files.
To open a Minitab Project that can include the session, worksheets, and graphs, select File Open Project.
FIGURE A1.6 Open Worksheet Dialog Box To save a worksheet, select File Save Current Worksheet As to display the Save Worksheet As dialog box, which is similar to the Open Worksheet As dialog box. Enter (or edit) the name of the file in the File name box and click the OK button. If applicable, you can also do the following: • •
Change to another folder by selecting that folder from the Save in drop-down list. Change the Save as type value to something other than the default choice, Minitab. “ Minitab Portable ” or an earlier version of Minitab, such as “ Minitab 13” are commonly chosen alternatives.
After saving your work, you should consider saving your file a second time, using a different name, in order to create a backup copy of your work. Files opened from nonwritable disks, such as the CD-ROM packaged with this text, cannot be saved to their original folders. To save a Minitab Project, select the similar File Save Project As. The Save Project As dialog box contains an Options button that displays a dialog box in which you can selectwhich project parts other than worksheets will be saved. Individual graphs and the session can also be saved separately by first selecting their windows and then selecting the similar File Save Graph As or File Save Session As , as appropriate. Minitab graphs can be saved in either a Minitab graph format or any one of several common graphics formats, and Session files can be saved as simple or formatted text files.
Printing Worksheets, Graphs, and Sessions To print a specific worksheet, graph, or session, f irst select the window of the worksheet, graph, or session to be printed. Then select File Print object , where object is
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
Appendix
either Worksheet , Graph, or Session Window, depending on the window you selected. If you are printing a graph or a session window, you will then see the Print dialog box. If you are printing a worksheet, you will first see a Data Window Print Options dialog box (Figure A1.7) that allows you to select formatting options for your printout (the default selections should be fine for most of your printouts). Click the OK button in that dialog box to proceed to the Print dialog box. The Print dialog box contains settings to select the printer to be used, what pages to print, and the number of copies to produce (1 is the default). If you need to change these settings, change them before clicking the OK button to produce your printout. After printing, you should verify the contents of your printout. Most printing failures will trigger the display of onscreen information that you can use to figure out the source of the failure. You can change the paper size or paper orientation of your printout by selecting File Page Setup and making the appropriate choices and clicking the OK button.
19
FIGURE A1.7 Data Window Print Options Dialog Box
X 6 5 8 3 1 8 5 5 0 : N B S I
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L. Berenson. Published by Prentice Hall.
I S B N : 0 5 5 8 1 3 8 5 6 X
Business Statistics: A First Course , Fourth Edition, by David M. Levine, Timothy C. Krehbiel, and Mark L.
Berenson. Published by Prentice Hall.
