Business Statistics : A First Course,9780130348272

Business Statistics : A First Course

by ; ;
Edition: 3rd
ISBN13: 9780130348272
ISBN10: 0130348279
Format: Paperback
Pub. Date: 2003-02-01
Publisher(s): Prentice Hall
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Summary

This book covers the concepts and applications of statistics used in the functional areas of business-accounting, marketing, management, economics, and finance. With a strong emphasis on concepts rather than on statistical methods, it shows readers how to properly use statistics to analyze data, demonstrates how computer software is an integral part of this analysis, and provides many exercises, cases and projects to support the learning process. Introduction and Data Collection. Presenting Data in Tables and Charts. Numerical Descriptive Measures. Basic Probability. Probability Distributions. Sampling Distributions and Confidence Intervals. Fundamentals of Hypothesis Testing: One-Sample Tests. Hypothesis Tests for Numerical Data from Two or More Samples. Hypothesis Tests for Categorical Data From Two or More Samples. Simple Linear Regression. Multiple Regression Analysis. Time Series Analysis. Statistical Applications in Quality and Productivity Management.

Table of Contents

Preface xv
Introduction and Data Collection
1(44)
Why a Manager Needs to Know About Statistics
2(2)
The Growth and Development of Modern Statistics
4(1)
What Readers of This Textbook Need to Know About Microsoft Excel and PHStat, Minitab, or SPSS®
5(1)
Why Data Are Needed
6(1)
Sources of Data
7(4)
Types of Data
11(3)
Design of Survey Research
14(2)
Types of Sampling Methods
16(6)
Evaluating Survey Worthiness
22(23)
Summary
27(1)
Key Terms
27(1)
Chapter Review Problems
27(3)
Case Study: Alumni Association Survey
30(1)
Basics of the Windows User Interface
31(2)
Introduction to Microsoft Excel
33(9)
Introduction to Minitab
42(1)
Introduction to SPSS®
43(2)
Presenting Data in Tables and Charts
45(54)
Organizing Numerical Data
46(4)
Tables and Charts for Numerical Data
50(8)
Graphing Bivariate Numerical Data
58(3)
Tables and Charts for Categorical Data
61(6)
Tabulating and Graphing Bivariate Categorical Data
67(4)
Graphical Excellence
71(28)
Summary
76(1)
Key Terms
76(1)
Chapter Review Problems
77(6)
The Springville Herald Case
83(2)
Using Microsoft Excel for Tables and Charts
85(6)
Using Minitab for Tables and Charts
91(3)
Using SPSS® for Tables and Charts
94(5)
Numerical Descriptive Measures
99(52)
Exploring Numerical Data and Their Properties
100(1)
Measures of Central Tendency, Variation, and Shape
101(20)
Exploratory Data Analysis
121(5)
Obtaining Descriptive Summary Measures from a Population
126(3)
The Coefficient of Correlation
129(5)
Pitfalls in Numerical Descriptive Measures and Ethical Issues
134(17)
Summary
135(1)
Key Terms
135(1)
Chapter Review Problems
136(6)
The Springville Herald Case
142(1)
Using Microsoft Excel for Descriptive Statistics
142(4)
Using Minitab for Descriptive Statistics
146(1)
Using SPSS® for Descriptive Statistics
147(4)
Basic Probability
151(24)
Basic Probability Concepts
153(8)
Conditional Probability
161(8)
Ethical Issues and Probability
169(6)
Summary
170(1)
Key Terms
171(1)
Chapter Review Problems
171(2)
Using Microsoft Excel for Basic Probability
173(2)
Probability Distributions
175(54)
The Probability Distribution for a Discrete Random Variable
176(3)
Covariance and Its Application in Finance
179(5)
Binomial Distribution
184(8)
The Normal Distribution
192(17)
Evaluating the Normality Assumption
209(20)
Summary
217(1)
Key Terms
217(1)
Chapter Review Problems
218(4)
The Springville Herald Case
222(1)
Using Microsoft Excel for the Covariance and for Probability Distributions
223(3)
Using Minitab with Probability Distributions
226(3)
Sampling Distributions and Confidence Interval Estimation
229(52)
Sampling Distributions
230(13)
Introduction to Confidence Interval Estimation
243(1)
Confidence Interval Estimation of the Mean (σ Known)
243(4)
Confidence Interval Estimation of the Mean (σ Unknown)
247(8)
Confidence Interval Estimation for the Proportion
255(3)
Determining Sample Size
258(7)
Confidence Interval Estimation and Ethical Issues
265(16)
Summary
266(1)
Key Terms
267(1)
Chapter Review Problems
267(5)
The Springville Herald Case
272(2)
Using Microsoft Excel for Sampling Distributions, Confidence Intervals, and Sample Size Determination
274(2)
Using Minitab for Sampling Distributions and Confidence Interval Estimation
276(3)
Using SPSS® for Confidence Interval Estimation
279(2)
Fundamentals of Hypothesis Testing: One-Sample Tests
281(38)
Hypothesis-Testing Methodology
282(5)
Z Test of Hypothesis for the Mean (σ Known)
287(7)
One-Tail Tests
294(3)
t Test of Hypothesis for the Mean (σ Unknown)
297(6)
Z Test of Hypothesis for the Proportion
303(4)
Potential Hypothesis-Testing Pitfalls and Ethical Issues
307(12)
Summary
309(2)
Key Terms
311(1)
Chapter Review Problems
311(3)
Using Microsoft Excel for One-Sample Tests of Hypothesis
314(1)
Using Minitab for One-Sample Tests of Hypothesis
315(2)
Using SPSS® for One-Sample Tests of Hypothesis
317(2)
Hypothesis Tests for Numerical Data from Two or More Samples
319(62)
Comparing Two Independent Samples: Tests for Differences in Two Means
320(10)
F Test for Differences in Two Variances
330(7)
Comparing Two Related Samples: Tests for the Mean Difference
337(9)
The Completely Randomized Design: One-Way Analysis of Variance
346(35)
Summary
361(1)
Key Terms
362(1)
Chapter Review Problems
362(7)
Case Study: Test-Marketing and Promoting a Ball-Point Pen
369(1)
The Springville Herald Case
370(2)
Using Microsoft Excel for Hypothesis Tests for Numerical Data from Two or More Samples
372(4)
Using Minitab for Hypothesis Tests for Numerical Data from Two or More Samples
376(2)
Using SPSS® for Hypothesis Tests for Numerical Data from Two or More Samples
378(3)
Hypothesis Tests for Categorical Data from Two or More Samples
381(38)
Z Test for the Difference Between Two Proportions
382(6)
χ2 Test for the Difference Between Two Proportions
388(7)
χ2 Test for Differences in More Than Two Proportions
395(6)
χ2 Test of Independence
401(18)
Summary
407(1)
Key Terms
408(1)
Chapter Review Problems
408(4)
The Springville Herald Case
412(2)
Using Microsoft Excel for Hypothesis Tests for Categorical Data from Two or More Samples
414(1)
Using Minitab for Hypothesis Tests for Categorical Data from Two or More Samples
415(1)
Using SPSS® for Hypothesis Tests for Categorical Data from Two or More Samples
416(3)
Simple Linear Regression
419(66)
Types of Regression Models
420(2)
Determining the Simple Linear Regression Equation
422(9)
Measures of Variation
431(5)
Assumptions
436(1)
Residual Analysis
437(5)
Measuring Autocorrelation: The Durbin-Watson Statistic
442(6)
Inferences About the Slope and Correlation Coefficient
448(7)
Estimation of Mean Values and Prediction of Individual Values
455(4)
Pitfalls in Regression and Ethical Issues
459(4)
Computations in Simple Linear Regression
463(22)
Summary
469(1)
Key Terms
469(1)
Chapter Review Problems
469(9)
Case Study: EastWestSide Movers
478(1)
The Springville Herald Case
478(1)
Using Microsoft Excel for Simple Linear Regression
479(2)
Using Minitab for Simple Linear Regression
481(2)
Using SPSS® for Simple Linear Regression
483(2)
Multiple Regression
485(80)
Developing the Multiple Regression Model
486(9)
Residual Analysis for the Multiple Regression Model
495(2)
Testing for the Significance of the Multiple Regression Model
497(2)
Inferences Concerning the Population Regression Coefficients
499(4)
Testing Portions of the Multiple Regression Model
503(8)
The Quadratic Regression Model
511(10)
Dummy-Variable Models
521(12)
Using Transformations in Regression Models
533(4)
Collinearity
537(2)
Model Building
539(11)
Pitfalls in Multiple Regression and Ethical Issues
550(15)
Summary
550(2)
Key Terms
552(1)
Chapter Review Problems
552(5)
Case Study: The Mountain States Potato Company
557(1)
Using Microsoft Excel for Multiple Regression
558(2)
Using Minitab for Multiple Regression
560(2)
Using SPSS® for Multiple Regression
562(3)
Time-Series Forecasting
565(60)
The Importance of Business Forecasting
566(1)
Component Factors of the Classical Multiplicative Time-Series Model
567(2)
Smoothing the Annual Time Series
569(7)
Least-Squares Trend Fitting and Forecasting
576(15)
Autoregressive Modeling for Trend Fitting and Forecasting
591(10)
Choosing an Appropriate Forecasting Model
601(5)
Time-Series Forecasting of Monthly or Quarterly Data
606(8)
Pitfalls Concerning Time-Series Forecasting
614(11)
Summary
615(1)
Key Terms
616(1)
Chapter Review Problems
616(3)
Case Study: Currency Trading
619(1)
The Springville Herald Case
619(1)
Using Microsoft Excel for Time-Series Forecasting
620(2)
Using Minitab for Time-Series Forecasting
622(1)
Using SPSS® for Time-Series Forecasting
623(2)
Statistical Applications in Quality and Productivity Management
625(100)
Quality and Productivity: A Historical Perspective
627(1)
Deming's 14 Points: A Theory of Management
627(3)
The Theory of Control Charts
630(2)
Control Chart for the Proportion of Nonconforming Items---The p Chart
632(6)
The Red Bead Experiment: Understanding Process Variability
638(3)
Control Charts for the Range (R) and the Mean (X)
641(36)
Summary
648(1)
Key Terms
648(1)
Chapter Review Problems
649(4)
Case Study: The Harnswell Sewing Machine Company Case
653(2)
The Springville Herald Case
655(2)
Using Microsoft Excel for Control Charts
657(1)
Using Minitab for Control Charts
658(1)
Using SPSS® for Control Charts
659(2)
Answers to Selected Even-Numbered Problems
661(16)
Appendices
A. Review of Arithmetic, Alegbra, and Logarithms
677(4)
B. Summation Notation
681(6)
C. Statistical Symbols and Greek Alphabet
687(2)
D. CD-ROM Contents
689(12)
E. Tables
701(20)
F. More About PHStat2
721(4)
Index 725

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