Statistics for managers using microsoft excel levine stephan krehbiel berenson

Discuss the practical implications of the test performed in following table: a. Manager 2, 85, 24, separate-variance t test? Master black belt , 24, The following table contains information regarding the Source: Data extracted from I. Using a 0,05 level of significance, is there a difference in Sample Standard "A School Size Mean Years Deviation ,nie the variability of salaries between managers and master black belts? Western 93 2. Based on the result of a , which t test defined in Section Eastern 4.

In , 58 sophomore business students were e. The larger the sales of a magazine, the more it can ing prediction line: charge advertisers. However, a circulation gap has appeared between the publishers' reports of magazines' newsstand sales and subsequent audits by the Audit Bureau of Circulations. The file t:! Jnnrrnfip contains the reported and. Interpret the meaning of the Yintercept, hu. Rosie Playboy Esquire TeenPeopie Interpret the meaning of the Y intercept, boo Source: Data extracted from M.

August 6, , b. AI, A Construct a scatter plot. For these data, bo Interpret the meaning of the slope, hJ, in this problem. Predict the audited newsstand sales for a magazine that predict the sales of pet food.

Assuming a linear relationship, use the least-squares 12 20 method to determine the regression coefficients bo and hi' c. Interpret the meaning of the slope, h], in this problem. Predict the labor hours for moving cubic feet. Interpret the meaning of the slope, b], in this problem. Predict the weekly sales of pet food for stores with 8 feet the time the customer enters the line until he or she is served.

The total number of a. Use the least-squares method to determine the regression recorded. The results are stored in e! Interpret the meaning of ho and hi in this problem. Assuming a linear relationship, use the least-squares d.

Predict the monthly rent for an apartment that has method to determine the regression coefficients bo and bl' 1, square feet. Interpret the meaning of the slope, hi, in this problem. Why would it not be appropriate to use the model to pre. Predict the waiting time when there are 20 customers in dict the monthly rent for apartments that have square the store. Your friends Jim and Jennifer are considering signing a The file They are trying to dec.

Construct a scatter plot The file c. Interpret the meaning of bo and b l in this problem. Predict the value of a baseball franchise that generates movies and the number of DVDs sold in thousands. The agent selects a sample of 25 d. Table for Problem Feet 1 14 1, 1, 2 1, 1, 15 1, 1, 3 1, 1, 16 1, 1, 4 1, 1, 17 1, 1, 5 18 1, 1, 6 1, 1, 19 1, 1, 7 1, 1, 20 1, 8 21 1, 1, 9 22 1, 1, 10 1, 23 1, Il 1, 1, 24 1, 12 1, 1, 25 1, 1, 13 2, 1, The first measure, the total sum of squares SST , is a measure of variation of the Yj values around their mean, Y.

The total variation, or total sum of squares, is subdivided into explained variation and unexplained variation. The standard error of the estimate represents a measure of the variation around the prediction line.

It is measured in the same units as the dependent variable Y. The interpretation of the standard error of the estimate is similar to that of the standard deviation.

Just as the standard deviation measures variability around the mean, the standard error of the estimate measures variability around the prediction line.

Using the results of that problem, a. How useful do you think this regression model is for of determination, ,. II1II keting manager used shelf space for pet food h. For those data, c. Determine the coefficient of determination, ,.

Determine the standard error of the estimate. How useful do you think this regression model is for Using the results of that problem, predicting sales? For those data, SSR , Can you think of other variables that might explain the pret its meaning.

Using the dicting audited sales? Using the results of that h. Can you think of other variables that might explain the b. X and l. From bel' or cubic! Lsing the result. Based your answers to a and b. X and r. At the a 0. Based on your answers to a and b. The data Using the results of that j1mblem.

From a. Compute the correlation coefficient by first computing ments. The data arc 1 ,. The data are stored in. From the gross to predict the sales of DVDs.

Using the results of that problem. Jal You can estimate the beta value of a stoc:k b N bl 0. The following table gives Index. What is its approximate market model?

Qut some beta values for some widely held stocks, using a year's b. What type of investors should be attracted to leveraged index funds? What type of investors should stay away pop- Ticker Symbol Beta from these funds? May Swirllatte whole milk pop-. For each of the six companies, interpret the beta value. How can investors use the beta value as a guide for Dunkin' Donuts Coffee Coolatta cream 1 are Starbucks Iced Coffee Mocha The beta values as described in Problem JlIne , p.

Two of the company's most popular funds are shown in the a. Compute and interpret the coefficient of correlation, r. January 7, Create this 11 Sample Mean 2.

B7 EG The data are stored in ItUmJ. Compare the results of a and b with those of Problem food. Which interval is wider? Chapter Review Problems Internet site one or more times between classes, the student a. Use the least-squares method to compute the regression was given a I for that time period. Predict the delivery time for cases of soft drink. The other three variables included the student's course d. Should you use the model to predict the delivery time for average, the student's cumulative grade point average a customer who is receiving cases of soft drink?

Why GPA , and the total number of hits the student had on the or why not? Internet site supporting the course. The following table gives e. Note explain its meaning in this problem. Perform a residual analysis. Source: Data extracted from D.

Baugher, A. JfJranelli, and E. Decision Sciences Journal of when business activity varies. Variable costs are added costs ;Innovative Education, 1 Fall The relationship can be characterized by the following equation: a. What conclusions can you reach from this correlation analysis? Are you surprised by the results, or are they consistent X Number of units of business activity with your own observations and experiences? In a leading managerial accounting textbook, the authors The hospital's total maintenance costs and able cost reflects the time required to unload the cases of number of patient-days for seven months are listed in the soft drink at the delivery point.

To begin, management following table and stored in IMMtilt! A sample of 20 deliveries within a territory was selected.

Brewer, R. Garrison, and E. Boston: 3 73 Using total maintenance costs as the dependent variable 7 Which regression coefficient represents fixed cost? Predict tOlal maintenance costs ft r a month with 7, of students III an rvt BA program based on iraduale patient -days.

The results are stored in I. A sample of 30 reccntly sold single-family houses in a small city is selected Hint: First, determine which are the independent and to study the relationship between selling price in thousands dependent variables. The a. Construct a scatter plot and. The results are in [t:r. Hint: First.

Use the prediction line developed in a to predict the a. Determine the coetfi cient of determination, ,. Interpret the meaning of the Y intercept, bu, and the slope, e. Use the prediction line developed in a to predict the f. Determine the coefficient of determination. Perform a residual analysis on your results and evaluate dent with a GMAT score of Data are collected from the past 32 working days, and the number of invoices processed and The assessed value in Hint: First, determine which are the independent and thousands of dollars and the heating area of the houses in dependent variables.

Assuming a linear relationship, use the least-squares in 1ml'! Interpret the meaning of the Y intercept. Hint: First, determine which are the independent and bJ, in this problem. Use the prediction line developed in a to predict the 51 a. Interpret the meaning of the Y intercept, b j, and the slope. Lt processed and also against time.

Based on the plots in e. Based on the results in e and f , what conclusions de square feet. Perform a residual analysis on your results and evaluate Prior to the b.

Engineers for Morton c. State the multiple regression equation. Interpret the meaning of the slopes. Explain why the regression coefficient, ho. Predict the monthly warehouse distribution cost When b. Data were collected from a I term impact , Two independent variables under consideration sample of 50 recent car models.

I a repeated impact test. Data are collected from a random sample of 15 types of currently manufactured running shoes, c. Explain why the regression coefficient, b o, has no practical meaning in the context of this problem. Predict the miles per gallon for cars that have 60 horsepower and weigh 2, pounds. Data were collected from a sample of22 cities ] r7SE'lFl Each city is allocated a specific maintains a centralized warehouse.

The sales of the product in thousands of dollars warehouse. Currently, a small handling fee is added to each results shown at the top of page and stored in fJ! Interpret the meaning of the regression coefficient. Which type of advertising is more effective?

Adjusted 1'2, and the Overall FTes! Predict the standby hours for a week in which the total 30 30 staff present have people-days and the remote hours 35 35 are Predict the appraised value for a house that has a land Ie '.

The area of 0. Id ,Total staff present XI -Weekly total of people-days f. In multiple regression, the coefficient of multiple determination represents the proportion of the variation in Y that is explained by the set of independent variables. I Problems for Section The Degrees of Sum of Mean dependent variable, team performance, was also given a Source Freedom Squares Squares F value of 1 through , with representing the highest Regression 2 60 rating.

Model 2 c. Determine whether there is a significant relationship between Yand the two independent variables at the 0. Model 3 e. Compute the adjusted r2. Interpret the adjusted r2 for each of the three models.

Error 10 Total 12 Determine the regression mean square MSR and the erties over time. Source Freedom Squares Squares F p-va.!! Compute the coefficient of multiple determination, ,. Error 12 0. Total 14 Determine whether there is a significant relationship Van Aken and Brian M. Interpret the meaning of the p-value. Management Journal, 4 , ]. The researchers d. Using the c. Using the results from that problem, ,compute the coefficient of multiple determination, r2, a.

Using the results from that problem, compute the coefficient of multiple determination, r2, a. Using the results from that problem, c. Residuals versus Xli ne 3. Residuals versus X 2i 4. Residuals versus time The first residual plot examines the pattern of residuals versus the predicted values of Y. If the residuals show a pattern for the predicted values of Y, there is evidence of a possible - :e curvilinear effect see Section I3 on page , andlor the need to transform the Y variable.

The second and third residual plots involve the independent variables. The fourth plot is used to investigate patterns in the residuals in order to validate the independence assumption when the data are collected in time order. Associated with this residual plot, as in Section Figure I statistic? On the ba,i, oj'lhc,c b. On the basis of these results from that problem, results, indicate the independent variables to include in a.

Which variable has the largest slope. Using the results from that problem. On the basis of these results. Using the results fWIll that pairs of shoes. Use the following results: problem, a. Variable Coefficient Error f Statistic b. Using the results from that prob! On the basis 1 f these r;sEi:F] I model for these data. Be sure to indicate the partlcu ar Shelf Space Weekly Sales models you need to evaluate and compare.

How do you 2 5 Front interpret this result? A random sample of 20 houses was selected, 11 20 Back For a through k , do 12 20 Front not include an interaction term. State the multiple regression equation that predicts the For a through m , do not include an interaction term.

State the multiple regression equation that predicts sales neighborhood. Interpret the regression coefficients in a. Predict the selling price for a house with nine rooms that is c.

Predict the weekly sales of pet food for a store with 8 located in an east-side neighborhood. Perform a residual analysis on the results and determine prediction interval. Perform a residual analysis on the results and determme e.

Is there a significant relationship between selling price whether the regression assumptions are valid. Is there a significant relationship between sales and the hood at the 0. Compare the slope in b with the slope for the simple selling price and neighborhood. Compute and interpret the adjusted r2. Explain the difference in the results. Compute the coefficients of partial determination and i.

Compute and interpret the meaning of the coefficient of interpret their meaning. What assumption do you need to make about the slope j. Compare r2 with the r2 value computed in Problem l. Add an interaction term to the model and, at the 0. Compute the coefficients of partial determination and nificant contribution to the model. On the basis of the results of f and I , which model is m. What assumption about the slope of shelf space With most appropriate? On the basis of the results of D and n , which model is Data are collected from a random sample of 12 equal-sized most appropriate?

Develop a regression model to to predict miles per gallon. Which regression model is more appropriate, the one used an Source: Extracted from Zagat Survey New York City Restaurants in this problem or the one used in Problem Develop a regression model to predict standby. Perform a residual analysis on the results and determine the interaction term makes a significant contribution to tion whether the regression assumptions are satisfied. Is there a significant relationship between price and the b.

Urs At the 0. The sion model for this set of data. Krehbiel, Miami University. Mark L. Index New to This Edition Enhanced statistical content including. The instructions for using Excel have been revised, reorganized, and enhanced in new end-of-chapter Excel Guides and back-of-the book Appendices. These sections support students by:. We have continued many of the traditions of past editions and have highlighted some of these features below:. Krehbiel, Miami University Mark L. New to This Edition Enhanced statistical content including A revised and simplified notation for test statistics in hypothesis testing.

A new chapter Chapter 18 that helps students apply the statistics learned in the previous 17 chapters to future real-world situations that require the analysis of data.

An expanded discussion of using PivotTables to summarize and explore multidimensional data. Even more illustrated and annotated worksheet results that are directly linked to specific step-by-step instructions. Help students see the relevance of statistics to their own careers by using examples from the functional areas that may become their areas of specialization.

Every statistical method is discussed using an example from a functional area, such as accounting, finance, management, or marketing, and explaining the application of methods to specific business activities. NEW - Business Analytics chapter Chapter 17 provides a complete introduction to the field of business analytics.

The chapter defines terms and categories that introductory business statistics students may encounter in other courses or outside the classroom. This capstone chapter brings the issues in First Things First scenarios full circle, and gives students the ability to apply business statistics to the real world. Several cases that reoccur throughout the book.

Case Studies offer realistic business scenarios to apply fundamental statistical and analytical concepts. Digital Cases ask students to examine interactive PDF documents and sift through claims and information in order to discover the data most relevant to a business case scenario. Students determine whether the conclusions and claims are supported by the data, and in doing so, they learn how to identify common misuses of statistical information.

Software integration and flexibility : Software instructions feature chapter examples and were personally written by the authors. With modularized Workbook, PHStat , and Analysis Toolbook instructions where applicable, both instructors and students can switch among these instruction sets as they use this book with no loss of statistical learning.

New to This Edition. New or revised Using Statistics case scenarios in seven chapters of the 9th Edition. These business scenarios begin each chapter, showing how statistics is used in accounting, finance, information systems, management, or marketing. A new Business Analytics chapter Chapter 17 provides a complete introduction to the field of business analytics. Tabular summaries now guide readers to reaching conclusions and making decisions based on statistical information.

Reach every student with MyLab Statistics Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience available within MyLab It lets students highlight and take notes all in one place — even when offline. Defining and Collecting Data 1. Organizing and Visualizing Variables 2.

Numerical Descriptive Measures 3. Basic Probability 4. Discrete Probability Distributions 5. Sampling Distributions 7. Confidence Interval Estimation 8. Two-Sample Tests Analysis of Variance Chi-Square and Nonparametric Tests Simple Linear Regression Introduction to Multiple Regression Multiple Regression Model Building Time-Series Forecasting Business Analytics Getting Ready to Analyze Data in the Future Statistical Applications in Quality Management online Decision Making Anybook Ltd.

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