Skip to content
Textbook Guides

Statistics For Managers Using Microsoft Excel, Global 8th Edition Solution Manual

Statistics For Managers Using Microsoft Excel, Global 8th Edition Solution Manual delivers clear and concise summaries of essential textbook content.

Preview 16 of 1341 pages

See the first 16 pages exactly as they appear in the document.

  1. Page 1
    Read page 1 as text

    Table of Contents Teaching Tips ................................ ................................ ................................ ................................ ... 1 Chapter 1 Defining and Collecting Data ................................ ................................ ............................... 39 Chapter 2 Organizing and Visualizing Variables ................................ ................................ ................. 46 Chapter 3 Numerical Descriptive Measures ................................ ................................ ..................... .. 141 Chapter 4 Basic Probability ................................ ................................ ................................ ................ 183 Chapter 5 Discrete Probability Distributions ................................ ................................ ...................... 190 Chapter 6 The Normal Distribution and Other Continuous Distributions ................................ .......... 21 5 Chapter 7 Sampling Distributions ................................ ................................ ................................ ....... 24 1 Chapter 8 Confidence Interval Estimation ................................ ................................ .......................... 26 1 Chapter 9 Fundamentals of Hypothesis Testing: One - Sample Tests ................................ .................. 29 2 Chapter 10 Two - Sample Tests ................................ ................................ ................................ ............. 3 37 Chapter 11 Analysis of Variance ................................ ................................ ................................ .......... 41 5 Chapter 12 Chi - Square and Nonparametric Tests ................................ ................................ ................ 44 1 Chapter 13 Simple Linear Regression ................................ ................................ ................................ .. 48 2 Chapter 14 Introduction to Multiple Regression ................................ ................................ .................. 5 2 1 Chapter 15 Multiple Regression Model Building ................................ ................................ ................. 5 84 Chapter 16 Time - Series Forecasting ................................ ................................ ................................ ..... 64 1 Chapter 17 Getting Ready to Analyze Data in the Future ................................ ................................ .... 696 Chapter 18 Statistical Applications in Quality Management (Online) ................................ ................. 748 Chapter 19 Decision Making (Online) ................................ ................................ ................................ .. 781 Online Sections ................................ ................................ ................................ .................. 820 Instructional Tips and Solutions for Digital Cases ................................ ............................. 883 The Brynne Packaging Case ................................ ................................ .............................. 918 The CardioGood Fitness Case ................................ ................................ ........................... 920

  2. Page 2
  3. Page 3
    Read page 3 as text

    The Choice Is Yours/More Descriptive Choices Follow - up Case ................................ .... 1 043 The Clear Mountain State Student Surveys Case ................................ ............................. 11 30 The Craybill Instrumentation Company Case ................................ ................................ .. 1 230 The Managing Ashland MultiComm Services Case ................................ ......................... 1 232 The Mountain States Potato Company Case ................................ ................................ .... 1287 The Sure Value Convenience Stores Case ................................ ................................ ........ 1 296

  4. Page 4
    Read page 4 as text

    Preface The first part of the Instructor’s Solutions Manual contains our educational philosophy and teaching tips for each chapter of the text. S olutions to End - of - Section Problems and Chapter Review Problems in each chapter follow. Instructional tips and solutions for the digital cases are included next . Answers to the Brynne Packaging Case, the CardioGood Fitness Case, the Choice Is Yours/More Descriptive Choices Follow - up Case , the Clear Mountain State Student Surveys Case , the Craybill Instrumentation Company Case , the Managing Ashland MultiComm Services Case, the Mountain States Potato Company Case and the Sure Value Convenience Stores Case are included last. The purpose of this Instructor’s Solutions Manual is to facilitate grading of assignments or exams by instructors and/or teaching assistants. Screen shots using output from PHStat are integrated throughout. Most of the problems are solved using PHStat. To present the steps involved in solving a problem, some intermediate numerical results are presented accurate to only a reasonable number of significant digits. Hence, instructors are reminded that the final results presented in this manual that are obtained using PHStat can sometimes be different from those obtained with a hand calculator computed using the intermediate values due to rounding.

  5. Page 5
    Read page 5 as text

    Teaching Tips for Statistics for Managers using Microsoft ® Excel 8 th Ed ition , Global Edition Our Starting Point Over a generation ago, advances in “data processing” led to new business opportunities as first centralized and then desktop computing proliferated. The Information Age was born. Computer science became much more than just an adjunct to a mathematics curri c ulum, and whole new fields of studies, such as computer information systems, emerged. More recently, further advances in information technologies have combined with data analysis techniques to create new opportunities in what is more data science than data processing or computer science. The world of business statistics has grown larger, bumping into other disciplines. And, in a reprise of something that occurred a generation ago, new fields of study, this time with names such as informatics, data analytics, and decision science, have emerged. This time of change makes what is taught in business statistics and how it is taught all the more critical. These new fields of study all share statistics as a foundation for further learning. We are accustomed to thinking about change, as seeking ways to continuously improve the teaching of business statistics have always guided our efforts. We actively participate in Decision Sciences Institute (DSI), American Statistical Association (ASA), and Making Statistics More Effective in Schools and Business (MSMESB) conferences. We use the ASA’s Guidelines for Assessment and Instruction (GAISE) reports and combine them with our experiences teaching business statistics to a diverse student body at several large universities. What to teach and how to teach it are particularly significant questions to ask during a time of change. As an author team, we bring a unique collection of experiences that we believe helps us find the proper perspective in balancing the old and the new. Our lead author, David M. Levine, was the first educator, along with Mark L. Berenson, to create a business statistics textbook that

  6. Page 6
    Read page 6 as text

    discussed using statistical software and incorporated “computer output” as illustrations — just the first of many teaching and curricular innov a tions in his many years of teaching business statistics. Our second author, David F. Stephan, developed courses and teaching methods in computer information systems and digital media during the information revolution, creating, and then teaching in, one of the first personal computer classrooms in a large school of business along the way. Early in his career, he introduced spreadsheet applications to a business statistics faculty audience that included David Levine, an introduction that would eventually led to the first edition of this textbook. Our newest co - author, Kathryn A. Szabat, has provided statistical advice to various business and non - business communities. Her background in statistics and o p erations research and her experiences interacting with professionals in practice have guided her, as departmental chair, in developing a new, interdisciplinary academic d e partment, Business Systems and Analytics, in response to the technology - and data - driven changes in business today. All three of us benefit from our many years teaching undergraduate business subjects and the diversity of interests and efforts of our past co - authors, Mark Berenson and Timothy Krehbiel. Two of us (Stephan and Szabat) also benefit from formal training and background in educational methods and instructional design. Educational Philosophy As in prior editions of Statistics for Managers Using Microsoft Excel , we are guided by these key learning principles: 1. Help students see the relevance of statistics to their own careers by providing examples drawn from the functional areas in which they may be specializing. Students need a frame of reference when learning statistics, especially when statistics is not their major. That frame of reference for business students should be the functional areas of business, such as accounting, finance, information systems, management, and marketing. Each statistics topic

  7. Page 7
    Read page 7 as text

    needs to be presented in an applied context related to at least one of these functional areas. The focus in teaching each topic should be on its application in business, the interpretation of results, the evaluation of the assumptions, and the discussion of what should be done if the assumptions are violated. 2. Emphasize interpretation of statistical results over mathematical computation. Introductory business statistics courses should recognize the growing need to interpret statistical results that computerized processes create. This makes the interpretation of results more important than knowing how to execute the tedious hand calculations required to produce them. 3. Give students ample practice in understanding how to apply statistics to business. Both classroom examples and homework exercises should involve actual or realistic data as much as possible. Students should work with data sets, both small and large, and be encouraged to look beyond the statistical analysis of data to the interpretation of results in a managerial context. 4. Familiarize students with how to use statistical software to assist business decision - making. Introductory business statistics courses should recognize that programs with statistical functions are commonly found on a business decision maker’s desktop computer. Integrating statistical software into all aspects of an introductory statistics course allows the course to focus on interpretation of results instead of computations (see point 2). 5. Provide clear instructions to students for using statistical applications. Books should explain clearly how to use programs such as Microsoft Excel with the study of statistics, without having those instructions dominate the book or distract from the learning of statistical concepts.

  8. Page 8
    Read page 8 as text

    First Things First In a time of change, you can never know exactly what knowledge and background students bring into an introductory business statistics classroom. Add that to the need to curb the fear factor about learning statistics that so many students begin with, and there’s a lot to cover even before you teach your first statistical concept. We created “First Things First” to meet this challenge. This unit sets the context for explaining what statistics is (not what students may think!) while ensuring that all students share an understanding of the forces that make learning business statistics critically important today. Especially designed for instructors teaching with course management tools, including those teaching hybrid or online courses, “First Things First” has been developed to be posted online or otherwise distributed before the first class section begins and is available from the download page for this book that is discussed in Appendix Section C.1. We would argue that the most important class is the first class. First impressions are critically important. You have the opportunity to set the tone to create a new impression that the course will be important to their business education. Make the following points: • T his course is not a math course. • State that you will be learning analytical skills for making business decisions. • Explain that the focus will be on how statistics can be used in the functional areas of business. This book uses a systematic approach for meeting a business objective or solving a business problem. This approach goes across all the topics in the book and most importantly can be used as a framework in real world situations when students graduate. The approach has the acronym DCOVA , which stands for D efine, C ollect, O rganize, V isualize, and A nalyze. • D efine the business objective or problem to be solved and then define the variables to be studied. • C ollect the data from appropriate sources • O rganize the data

  9. Page 9
    Read page 9 as text

    • V isualize the data by developing charts • A nalyze the data by using statistical methods to reach conclusions. To this, you can add C for Communicate which is critically important You can begin by emphasizing the importance of defining your objective or problem. Then, discuss the importance of operational definitions of variables to be considered and define variable, data, and statistics. Just as computers are used not just in the computer course, students need to know that statistics is used not just in the statistics course. This leads you to a discussion of business analytics in which data is used to make decisions. Make the point that analytics should be part of the competitive strategy of every organization especially since “big data” meaning data collect ed in huge volumes at very fast rates. need s to be analyzed. Inform the students that there is an Excel Guide at the end of each chapter. Strongly encourage or require students to read the Excel Guide at the end of this chapter so that they will be ready to use Excel with this book.

  10. Page 10
    Read page 10 as text

    Chapter 1 Y ou need to continue the discuss ion of the Define task by establishing the types of variables. Be sure to discuss the different types carefully since the ability to distinguish between categorical and numerical data will be crucial later in the course . Go over examples of each type of variable and have students provide examples of each type. Then, if you wish, you can cover the different measurement scales. Then move on to the C of the DCOVA approach, collecting data. Mention the different sources of data and make sure to cover the fact that data often needs to be cleaned of errors. Then, you could spend some time discussing sampling, you may want to take a bit more time and discuss the types of survey sampling methods and issues involved with survey sampling results. The Consider This essay discusses the important issue of the use of Web - based surveys. The chapter also introduces two continuing case s related to Managing Ashland MultiComm Services and CardioGood Fit ness that appear at the end of many chapters. The Digital case s are introduced in this chapter also. In these cases, students visit Web sites related to companies and issues raised in the Using Statistics scenarios that start each chapter. The goal of the Digital case s is for students to develop skills need ed to identify misuses of statistical information. As would be the situation with many real world cases, in Digital case s , students often need to sift through claims and assorted information in order to discover the data most relevant to a case task. They will then have to examine whether the conclusions and claims are supported by the data. (Instructional tips for using the Managing Ashland MultiComm Services and Digital case s and solutions to the Managing Ashland MultiComm Services and Digital case s are included in this Instructor’s Solutions Manual .) . M ake sure that students read the Excel Guide at the end of each chapter. Ways of Working With Excel on pages 7 and 8 explains the different type of Excel instructions. The Workbook instructions provide step - by - step instructions and live worksheets that automatically update when data changes. The PHSta t 2 add - in instructions provide instructions for using the PHStat2 add - in. Analysis ToolPak instructions provide instructions for using the Analysis ToolPak, the Excel add - in package that is included with many versions of Excel.

  11. Page 11
    Read page 11 as text

    Chapter 2 This chapter moves on to the organizing and visualizing steps of the DCOVA framework. I f you are going to collect sample data to use in Chapters 2 and 3, you can illustrate sampling by conducting a s urvey of students in your class. Ask each student to collect his or her own personal data concerning the time it takes to get ready to go to class in the morning or the time it takes to get to school or home from school. First, ask the students to write down a definition of how they plan to measure this time. Then, collect the various answers and read them to the class. Then, a single definition could be provided (such as the time to get ready is the time measured from when you get out of bed to when you leave your home, recorded to the nearest minute). In the next class, select a random sample of students and use the data collected (depending on the sample size) in class when Chapters 2 and 3 are discussed. Then, move on to the Organize step that involves setting up your data in an Excel worksheet and develop tables to help you prepare charts and analyze your data. Begin your discussion for categorical data with the example on p. 34 concerning how people pay for purchases and other transactions . Show the summary table and then if you wish, explain that you can sometimes organize the data into a two - way table that has one variable in the row and another in the column. Continue with organizing data (but now for numerical data) by referring to the cost of a restaurant meal on p. 38 . Show the simple ordered array and how a frequency distribution, percentage distribution , or cumulative distribution can summarize the raw data in a way that is more useful. Now you are ready to tackle the Visualize step. A good way of starting this part of the chapter is to display the following quote. " A picture is worth a thousand words." Students will almost certainly be familiar with Microsoft ® Word and may have already used Excel to construct charts that they have pasted into Word documents. Now you will be using Excel to construct many different types of charts. Return to the purchase payment data previously discussed and illustrate how a bar chart , pie , and doughnut chart can be constructed using Excel . Mention the advantages and disadvantages of each chart . A good example is to show the data on

  12. Page 12
    Read page 12 as text

    incomplete ATM transactions on p. 49 and how the Pareto chart enables you to focus on the vital few categories. If time permits, you can discuss the side - by - side bar chart for a contingency table. To examine charts for numerical variables you can either use the restaurant data previously mentioned , the retirement funds data , or data that you have collected from your class. You may want to begin with a simple stem - and - leaf display that both organizes the data and shows a bar type chart. Then move on to the histogram and the various polygons, pointing out the advantages and disadvantages of each. If time permits, you can discuss the scatter plot and the time - series plot for two numerical variables. Otherwise, you can wait until you get to regression analysis. If you cover the time series plot, you might also want to mention sparklines that are discussed in Section 2.6. Also, if possible, you may want to discuss how multidimensional tables allow you to drill down to individual cells of the table. You can follow this with further discussion of PivotTables and Excel slicers that enable you to see panels for each variable being studied. If the opportunity is available, we believe that it is worth the time to cov er Section 2. 7 on Challenges in Organizing and Visualizing Variables . This is a topic that students very much enjoy since it allows for a great deal of classroom interaction. After discussing the fundamental principles of good graph s , try to illustrate some of the improper displays shown in Figures 2. 26 – 2. 2 8 . Ask students what is “bad” about these figures. Follow up with a homework assignment involving Problems 2. 69 – 2. 73 ( USA Today is a great source). You will find that the chapter review problems provide large data sets with numerous variables. Report writing exercises provide the opportunity for students to integrate written and or oral presentation with the statistics they have learned. The Managing Ashland MultiComm Services case enables students to examine the use of statistics in an actual business environment. The Digital case refers to the EndRun Financial Service s and claims that have been made. The CardioGood Fitness case focuses on developing a customer profile for a market research team. The Choice Is Yours Follow - up expands on the chapter discussion of the mutual funds data. The Clear Mountain State Student Survey provides data collected from a sample of undergraduate students. The Excel Guide for this and the remaining chapters are organized according to the sections of the chapter. It is quite extensive since it covers both organizing and visualizing many different graphs. The Excel Guide includes instructions for Workbook , PHStat2, and the Analysis ToolPak.

  13. Page 13
    Read page 13 as text

    Chapter 3 This chapter on descriptive numerical statistical measures represents the initial presentation of statistical symbols in the text. Students who need to review arithmetic and algebraic concepts may wish to refer to Appendix A for a quick review or to appropriate texts (see www. p earson .com ) or videos ( www.videoaidedinstruction.com ). Once again, as with the tables and charts construct ed for numerical data, it is useful to provide an interesting set of data for classroom discussion. If a sample of students was selected earlier in the semester and data concerning student time to get ready or commuting time was collected (see Chapters 1 and 2), use these data in developing the numerous descriptive summary measures in this chapter. (If they have not been developed, use other data for classroom illustration.) Discussion of the chapter begins with the property of central tendency. We have found that almost all students are familiar with the arithmetic mean (which they know as the average) and most students are familiar with the median. A good way to begin is to compute the mean for your classroom example. Emphasize the effect of extreme values on the arithmetic mean and point out that the mean is like the center of a seesaw -- a balance point. Note that you will return to this concept later when you discuss the variance and the standard deviation. You might want to introduce summation notation at this point and express the arithmetic mean in formula notation as in Equation (3.1). (Alternatively, you could wait until you cover the variance and standard deviation.) A classroom example in which summation notation is reviewed is usually worthwhile. Remind the students again that Appendix A includes a review of arithmetic and algebra and summation notation [or refer them to other text sources such as those found at www. p earson .com or videos (see www. videoaidedinstruction.com )]. The next statistic to compute is the median. Be sure to remind the students that the median as a measure of position must have all the values ranked in order from lowest to highest. Be sure to have the students compare the arithmetic mean to the median and explain that this tells us something about another property of data (skewness). Following the median, the mode can be briefly discussed. Once again, have the students compare this result to those of the arithmetic mean and median for your data set. If time permits, you can also discuss the geometric mean which is heavily used in finance. The completion of the discussion of central tendency leads to the second characteristic of data, variability. Mention that all measures of variation have several things in common: (1) they can never be negative, (2) they will be equal to 0 when all items are the same, (3) they will be small when there isn't much variation, and (4) they will be large when there is a great deal of variation.

  14. Page 14
    Read page 14 as text

    The first measure of variability to consider is the simplest one, the range. Be sure to point out that the range only provides information about the extremes, not about the distribution between the extremes. P oint out that the range lack s one important ingredient, the ability to take into account each data value. Bring up the idea of computing the differences around the mean, but then return to the fact that as the balance point of the seesaw, these differences add up to zero. At that point, ask the students what they can do mathematically to remove the negative sign for some of the values. Most likely, they will answer by telling you to square them (although someone may realize that the absolute value could be taken). Next, you may want to define the squared differences as a sum of squares. Now you need to have the students realize that the number of value s being considered affects the magnitude of the sum of squared differences. Therefore, it makes sense to divide by the number of value s and compute a measure called the variance. If a population is involved, you divide by N , the population size, but if you are using a sample, you divide by n - 1, to make the sample result a better estimate of the population variance. You can finish the development of variation by noting that since the variance is in squared units, you need to take the square root to compute the standard deviation. Another measure of variation that can be discussed is the coefficient of variation. Be sure to illustrate the usefulness of this as a measure of relative variation by using an example in which two data sets have vastly different standard deviations, but also vastly different means. A good example is one that involves the volatility of stock prices. Point out that the variation of the price should be considered in the context of the magnitude of the arithmetic mean. The final measure of variation is the Z score. Point out that this provides a measure of variation in standard deviation units. You can also say that you will return to Z scores in Chapter 6 when the normal distribution will be discussed. You are now ready to move on to the third characteristic of data, shape . Be sure to clearly define and illustrate both symmetric and skewed distributions by comparing the mean and median. You may also want to briefly mention the property of kurtosis which is the relative concentration of values in the center of the distribution as compared to the tails. This statistic is provided by Excel through an Excel function or the Analysis Toolpak . Once these three characteristics have been discussed, you are ready to show how they can be computed using Excel. Now that these measures are understood , you can further explore data by computing the quartiles, the interquartile range, the five number summary, and constructing a boxplot . You begin by determining the quartiles. Reference here can be made to the standardized exams that students have taken, and the quantile scores that they have received (97th percentile, 48th

  15. Page 15
    Read page 15 as text

    percentile , 12th percentile , etc. ). Explain that the 1 st and 3 rd quartiles are merely two special quantiles -- the 25th and 75th, that unlike the median (the 2 nd quartile) , are not at the center of the distribution. Once the quartiles have been computed, the interquartile range can be de termin ed. Mention that the interquartile range computes the variation in the center of the distribution as compared to the difference in the extremes computed by the range. You can then discuss the five - number summary of minimum value, first quartile, median, third quartile, and maximum value. Then, you construct the boxplot. Present this plot from the perspective of serving as a tool for determining the location, variability, and symmetry of a distribution by visual inspection, and as a graphical tool for comparing the distribution of several groups. It is useful to display Figure 3. 6 on page 118 that indicates the shape of the boxplot for four different distributions. Then, use PHStat2 to construct a boxplot. Note that you can construct the boxplot for a single group or for multiple groups. If you desire, you can discuss descriptive measures for a population and introduce the empirical rule and the Chebyshev rule. If time permits, and you have covered scatter plot s in Chapter 2, you can briefly discuss the covariance and the coefficient of correlation as a measure of the strength of the association between two numerical variables. Point out that the coefficient of correlation has the advantage as compared to the covariance of being on a scale that goes from - 1 to +1. Figure 3. 9 on p. 1 27 is useful in depicting scatter plot s for different coefficients of correlation. Once again, you will find that the chapter review problems provide large data sets with numerous variables. The Managing Ashland MultiComm Services case enables students to examine the use of descriptive statistics in an actual business environment. The Digital case continues the evaluation of the EndRun Financial Service s discussed in the Digital case in Chapter 2. The CardioGood Fitness case focuses on developing a customer profile for a market research team. More Descriptive Choices Follow - up expands on the discussion of the mutual funds data. The Clear Mountain State Student Survey provides data collected from a sample of undergraduate students. The Excel Guide for the chapter includes instructions on using different Excel functions to compute various statistics. Alternatively, you can use PHStat or the Analysis ToolPak to compute a list of statistics. PHStat2 can be used to construct a boxplot.

  16. Page 16
    Read page 16 as text

    Chapter 4 The chapter on probability represents a bridge between the descriptive statistics already covered and the topics of statistical inference, regression, time series, and business analytics to be covered in subsequent chapters. In many traditional statistics courses, often a great deal of time is spent on probability topics that are of little direct applicability in basic statistics. The approach in this text is to cover only those topics that are of direct applicability in the remainder of the text. You need to begin with a relatively concise discussion of some probability rules. Essentially, students really just need to know that (1) no probability can be negative, (2) no probability can be more than 1, and (3) the sum of the probabilities of a set of mutually exclusive events adds to 1.0. Students often understand the subject best if it is taught intuitively with a minimum of formulas, with an example that relates to a business application shown as a two - way contingency table (see the Using Statistics example). If desired, you can use the Excel Workbook instructions or PHStat2 to compute probabilities from the contingency table. Once these basic elements of probability have been discussed, if there is time and you desire, conditional probability and Bayes ’ theorem (an online topic) can be covered. The Consider This concerning email SPAM is a wonderful way of helping student s realize the application of probability to everyday life. Be aware that in a one - semester course where time is particularly limited, these topics may be of marginal importance. The Digital case in this chapter extends the evaluation of the EndRun Financial Service s to consider claims made about various probabilities. The CardioGood Fitness, More Descriptive Choices Follow - up, and Clear Mountain State Student Survey each involve developing contingency tables to be able to compute and interpret conditional and marginal probabilities.

1325 more pages in the full document

Unlock it once and it stays in your library, ready to chat with or turn into flashcards.

Unlock the full document

More Statistics study materials

See all

Study this document with CramX

Once it is in your library, every tool can work from it.