Business statistics: a first course

By:

Levine, David M

Contributor(s):

Material type: Text

TextPublication details: USA PRENTICE HALL 2000Edition: 2nd edDescription: 654p., 260 x 210mm, Colour illustrations, paperbackISBN:

0130867543

Subject(s):

Business Development

Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Standard Loan	Thurles Library Main Collection	519.502 LEV (Browse shelf(Opens below))	Available		R04116KKRCT

Enhanced descriptions from Syndetics:

This text covers the concepts and applications of statistics used in the functional areas of business, accounting, marketing, management, economics, and finance. Thoroughly revised to shift its emphasis more on concepts than statistical methods, it shows students 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. For a one term course in Business Statistics at either the undergraduate or graduate level. Written for those whose who teach a one-term course and prefer a briefer book. *Briefer coverage. *Presents a less computational, more interpretational approach to statistical concepts and data analysis. *Integrates numerous examples of computer output from both Excel and Minitab within the chapters. *A complete new chapter on Multiple Regression - Emphasizes model building. *Greater emphasis on applications to the functional areas of business. *Retooled exercise sets use real data wherever possible. *Student CD-ROM packaged free with each copy of the book. *This custom designed web site contains many resources for both students and i

This work covers the concepts and applications of statistics used in functional areas of business accounting, marketing, management, economics and finance. The emphasis leans more toward the conceptual side rather than the methodical.

Table of contents provided by Syndetics

Preface (p. xv)
1 Introduction and Data Collection (p. 1)
1.1 Why a Manager Needs to Know About Statistics (p. 2)
1.2 The Growth and Development of Modern Statistics (p. 4)
1.3 What Readers of This Textbook Need to Know About Microsoft Excel and PHStat, Minitab, or SPSS (p. 5)
1.4 Why Data Are Needed (p. 6)
1.5 Sources of Data (p. 7)
1.6 Types of Data (p. 11)
1.7 Design of Survey Research (p. 14)
1.8 Types of Sampling Methods (p. 16)
1.9 Evaluating Survey Worthiness (p. 22)
Summary (p. 27)
Key Terms (p. 27)
Chapter Review Problems (p. 27)
Case Study: Alumni Association Survey (p. 30)
A.1.1 Basics of the Windows User Interface (p. 31)
A.1.2 Introduction to Microsoft Excel (p. 33)
A.1.3 Introduction to Minitab (p. 42)
A.1.4 Introduction to SPSS (p. 43)
2 Presenting Data in Tables and Charts (p. 45)
2.1 Organizing Numerical Data (p. 46)
2.2 Tables and Charts for Numerical Data (p. 50)
2.3 Graphing Bivariate Numerical Data (p. 58)
2.4 Tables and Charts for Categorical Data (p. 61)
2.5 Tabulating and Graphing Bivariate Categorical Data (p. 67)
2.6 Graphical Excellence (p. 71)
Summary (p. 76)
Key Terms (p. 76)
Chapter Review Problems (p. 77)
The Springville Herald Case (p. 83)
A.2.1 Using Microsoft Excel for Tables and Charts (p. 85)
A.2.2 Using Minitab for Tables and Charts (p. 91)
A.2.3 Using SPSS for Tables and Charts (p. 94)
3 Numerical Descriptive Measures (p. 99)
3.1 Exploring Numerical Data and Their Properties (p. 100)
3.2 Measures of Central Tendency, Variation, and Shape (p. 101)
3.3 Exploratory Data Analysis (p. 121)
3.4 Obtaining Descriptive Summary Measures from a Population (p. 126)
3.5 The Coefficient of Correlation (p. 129)
3.6 Pitfalls in Numerical Descriptive Measures and Ethical Issues (p. 134)
Summary (p. 135)
Key Terms (p. 135)
Chapter Review Problems (p. 136)
The Springville Herald Case (p. 142)
A.3.1 Using Microsoft Excel for Descriptive Statistics (p. 142)
A.3.2 Using Minitab for Descriptive Statistics (p. 146)
A.3.3 Using SPSS for Descriptive Statistics (p. 147)
4 Basic Probability (p. 151)
4.1 Basic Probability Concepts (p. 153)
4.2 Conditional Probability (p. 161)
4.3 Ethical Issues and Probability (p. 169)
Summary (p. 170)
Key Terms (p. 171)
Chapter Review Problems (p. 171)
A.4.1 Using Microsoft Excel for Basic Probability (p. 173)
5 Probability Distributions (p. 175)
5.1 The Probability Distribution for a Discrete Random Variable (p. 176)
5.2 Covariance and Its Application in Finance (p. 179)
5.3 Binomial Distribution (p. 184)
5.4 The Normal Distribution (p. 192)
5.5 Evaluating the Normality Assumption (p. 209)
Summary (p. 217)
Key Terms (p. 217)
Chapter Review Problems (p. 218)
The Springville Herald Case (p. 222)
A.5.1 Using Microsoft Excel for the Covariance and for Probability Distributions (p. 223)
A.5.2 Using Minitab with Probability Distributions (p. 226)
6 Sampling Distributions and Confidence Interval Estimation (p. 229)
6.1 Sampling Distributions (p. 230)
6.2 Introduction to Confidence Interval Estimation (p. 243)
6.3 Confidence Interval Estimation of the Mean ([sigma] Known) (p. 243)
6.4 Confidence Interval Estimation of the Mean ([sigma] Unknown) (p. 247)
6.5 Confidence Interval Estimation for the Proportion (p. 255)
6.6 Determining Sample Size (p. 258)
6.7 Confidence Interval Estimation and Ethical Issues (p. 265)
Summary (p. 266)
Key Terms (p. 267)
Chapter Review Problems (p. 267)
The Springville Herald Case (p. 272)
A.6.1 Using Microsoft Excel for Sampling Distributions, Confidence Intervals, and Sample Size Determination (p. 274)
A.6.2 Using Minitab for Sampling Distributions and Confidence Interval Estimation (p. 276)
A.6.3 Using SPSS for Confidence Interval Estimation (p. 279)
7 Fundamentals of Hypothesis Testing: One-Sample Tests (p. 281)
7.1 Hypothesis-Testing Methodology (p. 282)
7.2 Z Test of Hypothesis for the Mean ([sigma] Known) (p. 287)
7.3 One-Tail Tests (p. 294)
7.4 @t Test of Hypothesis for the Mean ([sigma] Unknown) (p. 297)
7.5 Z Test of Hypothesis for the Proportion (p. 303)
7.6 Potential Hypothesis-Testing Pitfalls and Ethical Issues (p. 307)
Summary (p. 309)
Key Terms (p. 311)
Chapter Review Problems (p. 311)
A.7.1 Using Microsoft Excel for One-Sample Tests of Hypothesis (p. 314)
A.7.2 Using Minitab for One-Sample Tests of Hypothesis (p. 315)
A.7.3 Using SPSS for One-Sample Tests of Hypothesis (p. 317)
8 Hypothesis Tests for Numerical Data from Two or More Samples (p. 319)
8.1 Comparing Two Independent Samples: Tests for Differences in Two Means (p. 320)
8.2 F Test for Differences in Two Variances (p. 330)
8.3 Comparing Two Related Samples: Tests for the Mean Difference (p. 337)
8.4 The Completely Randomized Design: One-Way Analysis of Variance (p. 346)
Summary (p. 361)
Key Terms (p. 362)
Chapter Review Problems (p. 362)
Case Study: Test-Marketing and Promoting a Ball-Point Pen (p. 369)
The Springville Herald Case (p. 370)
A.8.1 Using Microsoft Excel for Hypothesis Tests for Numerical Data from Two or More Samples (p. 372)
A.8.2 Using Minitab for Hypothesis Tests for Numerical Data from Two or More Samples (p. 376)
A.8.3 Using SPSS for Hypothesis Tests for Numerical Data from Two or More Samples (p. 378)
9 Hypothesis Tests for Categorical Data from Two or More Samples (p. 381)
9.1 Z Test for the Difference Between Two Proportions (p. 382)
9.2 X[superscript 2] Test for the Difference Between Two Proportions (p. 388)
9.3 X[superscript 2] Test for Differences in More Than Two Proportions (p. 395)
9.4 X[superscript 2] Test of Independence (p. 401)
Summary (p. 407)
Key Terms (p. 408)
Chapter Review Problems (p. 408)
The Springville Herald Case (p. 412)
A.9.1 Using Microsoft Excel for Hypothesis Tests for Categorical Data from Two or More Samples (p. 414)
A.9.2 Using Minitab for Hypothesis Tests for Categorical Data from Two or More Samples (p. 415)
A.9.3 Using SPSS for Hypothesis Tests for Categorical Data from Two or More Samples (p. 416)
10 Simple Linear Regression (p. 419)
10.1 Types of Regression Models (p. 420)
10.2 Determining the Simple Linear Regression Equation (p. 422)
10.3 Measures of Variation (p. 431)
10.4 Assumptions (p. 436)
10.5 Residual Analysis (p. 437)
10.6 Measuring Autocorrelation: The Durbin-Watson Statistic (p. 442)
10.7 Inferences About the Slope and Correlation Coefficient (p. 448)
10.8 Estimation of Mean Values and Prediction of Individual Values (p. 455)
10.9 Pitfalls in Regression and Ethical Issues (p. 459)
10.10 Computations in Simple Linear Regression (p. 463)
Summary (p. 469)
Key Terms (p. 469)
Chapter Review Problems (p. 469)
Case Study: EastWestSide Movers (p. 478)
The Springville Herald Case (p. 478)
A.10.1 Using Microsoft Excel for Simple Linear Regression (p. 479)
A.10.2 Using Minitab for Simple Linear Regression (p. 481)
A.10.3 Using SPSS for Simple Linear Regression (p. 483)
11 Multiple Regression (p. 485)
11.1 Developing the Multiple Regression Model (p. 486)
11.2 Residual Analysis for the Multiple Regression Model (p. 495)
11.3 Testing for the Significance of the Multiple Regression Model (p. 497)
11.4 Inferences Concerning the Population Regression Coefficients (p. 499)
11.5 Testing Portions of the Multiple Regression Model (p. 503)
11.6 The Quadratic Regression Model (p. 511)
11.7 Dummy-Variable Models (p. 521)
11.8 Using Transformations in Regression Models (p. 533)
11.9 Collinearity (p. 537)
11.10 Model Building (p. 539)
11.11 Pitfalls in Multiple Regression and Ethical Issues (p. 550)
Summary (p. 550)
Key Terms (p. 552)
Chapter Review Problems (p. 552)
Case Study: The Mountain States Potato Company (p. 557)
A.11.1 Using Microsoft Excel for Multiple Regression (p. 558)
A.11.2 Using Minitab for Multiple Regression (p. 560)
A.11.3 Using SPSS for Multiple Regression (p. 562)
12 Time-Series Forecasting (p. 565)
12.1 The Importance of Business Forecasting (p. 566)
12.2 Component Factors of the Classical Multiplicative Time-Series Model (p. 567)
12.3 Smoothing the Annual Time Series (p. 569)
12.4 Least-Squares Trend Fitting and Forecasting (p. 576)
12.5 Autoregressive Modeling for Trend Fitting and Forecasting (p. 591)
12.6 Choosing an Appropriate Forecasting Model (p. 601)
12.7 Time-Series Forecasting of Monthly or Quarterly Data (p. 606)
12.8 Pitfalls Concerning Time-Series Forecasting (p. 614)
Summary (p. 615)
Key Terms (p. 616)
Chapter Review Problems (p. 616)
Case Study: Currency Trading (p. 619)
The Springville Herald Case (p. 619)
A.12.1 Using Microsoft Excel for Time-Series Forecasting (p. 620)
A.12.2 Using Minitab for Time-Series Forecasting (p. 622)
A.12.3 Using SPSS for Time-Series Forecasting (p. 623)
13 Statistical Applications in Quality and Productivity Management (p. 625)
13.1 Quality and Productivity: A Historical Perspective (p. 627)
13.2 Deming's 14 Points: A Theory of Management (p. 627)
13.3 The Theory of Control Charts (p. 630)
13.4 Control Chart for the Proportion of Nonconforming Items--The p Chart (p. 632)
13.5 The Red Bead Experiment: Understanding Process Variability (p. 638)
13.6 Control Charts for the Range (R) and the Mean (X) (p. 641)
Summary (p. 648)
Key Terms (p. 648)
Chapter Review Problems (p. 649)
Case Study: The Harnswell Sewing Machine Company Case (p. 653)
The Springville Herald Case (p. 655)
A.13.1 Using Microsoft Excel for Control Charts (p. 657)
A.13.2 Using Minitab for Control Charts (p. 658)
A.13.3 Using SPSS for Control Charts (p. 659)
Answers to Selected Even-Numbered Problems (p. 661)
Appendices
A. Review of Arithmetic, Alegbra, and Logarithms (p. 677)
B. Summation Notation (p. 681)
C. Statistical Symbols and Greek Alphabet (p. 687)
D. CD-ROM Contents (p. 689)
E. Tables (p. 701)
F. More About PHStat2 (p. 721)
Index (p. 725)