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Basic Statistics for Business and Economics with Student CD-ROM,9780073121659
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Basic Statistics for Business and Economics with Student CD-ROM

by ; ;
Edition:
5th
ISBN13:

9780073121659

ISBN10:
0073121657
Format:
Hardcover
Pub. Date:
1/18/2005
Publisher(s):
McGraw-Hill/Irwin
List Price: $160.05

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Summary

The Fifth Edition of Basic Statistics for Business and Economics is a shorter version of Lind/Marchal/Wathen's Statistical Techniques in Business and Economics, 12e. The authors of this text continue to provide a student-oriented approach to business statistics. In this book you will find step-by-step solved examples, realistic exercises, and up-to-date technology and illustrations. Book jacket.

Table of Contents

What Is Statistics?
1(22)
Introduction
2(1)
Why Study Statistics?
2(2)
What Is Meant by Statistics?
4(2)
Types of Statistics
6(3)
Descriptive Statistics
6(1)
Inferential Statistics
7(2)
Types of Variables
9(1)
Levels of Measurement
9(5)
Nominal-Level Data
10(1)
Ordinal-Level Data
11(1)
Interval-Level Data
12(1)
Ratio-Level Data
12(2)
Exercises
14(1)
Statistics, Graphics, and Ethics
15(3)
Misleading Statistics
15(1)
Association Does Not Necessarily Imply Causation
15(1)
Graphs Can Be Misleading
16(1)
Become a Better Consumer and a Better Producer of Information
17(1)
Ethics
17(1)
Software Applications
18(1)
Chapter Outline
19(1)
Chapter Exercises
19(1)
exercises.com
20(1)
Dataset Exercises
21(1)
Answers to Self-Review
22(1)
Describing Data: Frequency Distributions and Graphic Presentation
23(34)
Introduction
24(1)
Constructing a Frequency Distribution
25(4)
Class Intervals and Class Midpoints
29(1)
A Software Example
29(1)
Relative Frequency Distribution
30(1)
Exercises
31(1)
Graphic Presentation of a Frequency Distribution
32(5)
Histogram
32(2)
Frequency Polygon
34(3)
Exercises
37(4)
Cumulative Frequency Distributions
38(3)
Exercises
41(1)
Other Graphic Presentations of Data
42(4)
Line Graphs
42(1)
Bar Charts
43(1)
Pie Charts
44(2)
Exercises
46(1)
Chapter Outline
47(1)
Chapter Exercises
48(5)
exercises.com
53(1)
Dataset Exercises
53(1)
Software Commands
54(2)
Answers to Self-Review
56(1)
Describing Data: Numerical Measures
57(36)
Introduction
58(1)
The Population Mean
59(1)
The Sample Mean
60(1)
Properties of the Arithmetic Mean
61(1)
Exercises
62(1)
The Weighted Mean
63(1)
Exercises
64(1)
The Median
64(1)
The Mode
65(2)
Exercises
67(1)
Software Solution
68(1)
The Relative Positions of the Mean, Median, and Mode
68(2)
Exercises
70(1)
The Geometric Mean
71(1)
Exercises
72(1)
Why Study Dispersion?
73(1)
Measures of Dispersion
74(2)
Range
74(1)
Mean Deviation
75(1)
Exercises
76(3)
Variance and Standard Deviation
77(2)
Exercises
79(1)
Software Solution
80(1)
Exercises
81(1)
Interpretation and Uses of the Standard Deviation
82(2)
Chebyshev's Theorem
82(1)
The Empirical Rule
83(1)
Exercises
84(1)
Chapter Outline
84(2)
Pronunciation Key
86(1)
Chapter Exercises
86(3)
exercises.com
89(1)
Dataset Exercises
90(1)
Software Commands
90(2)
Answers to Self-Review
92(1)
Describing Data: Displaying and Exploring Data
93(27)
Introduction
94(1)
Dot Plots
94(2)
Exercises
96(1)
Quartiles, Deciles, and Percentiles
97(3)
Exercises
100(1)
Box Plots
100(2)
Exercises
102(1)
Skewness
103(4)
Exercises
107(1)
Describing the Relationship between Two Variables
107(3)
Exercises
110(2)
Chapter Outline
112(1)
Pronunciation Key
112(1)
Chapter Exercises
112(4)
exercises.com
116(1)
Dataset Exercises
116(1)
Software Commands
117(2)
Answers to Self-Review
119(1)
A Survey of Probability Concepts
120(36)
Introduction
121(1)
What Is a Probability?
122(2)
Approaches to Assigning Probabilities
124(3)
Classical Probability
124(1)
Empirical Probability
125(1)
Subjective Probability
126(1)
Exercises
127(1)
Some Rules for Computing Probabilities
128(5)
Rules of Addition
128(5)
Exercises
133(4)
Rules of Multiplication
134(3)
Contingency Tables
137(2)
Tree Diagrams
139(2)
Exercises
141(1)
Principles of Counting
142(4)
The Multiplication Formula
142(1)
The Permutation Formula
143(2)
The Combination Formula
145(1)
Exercises
146(1)
Chapter Outline
147(1)
Pronunciation Key
148(1)
Chapter Exercises
148(4)
exercises.com
152(1)
Dataset Exercises
152(1)
Software Commands
153(1)
Answers to Self-Review
154(2)
Discrete Probability Distributions
156(29)
Introduction
157(1)
What Is a Probability Distribution?
157(2)
Random Variables
159(1)
Discrete Random Variable
159(1)
Continuous Random Variable
160(1)
The Mean, Variance, and Standard Deviation of a Probability Distribution
160(3)
Mean
160(1)
Variance and Standard Distribution'
161(2)
Exercises
163(1)
Binomial Probability Distribution
164(6)
How Is a Binomial Probability Distribution Computed
165(2)
Binomial Probability Tables
167(3)
Exercises
170(3)
Cumulative Binomial Probability Distributions
172(1)
Exercises
173(1)
Poisson Probability Distribution
174(3)
Exercises
177(1)
Chapter Outline
177(1)
Chapter Exercises
178(4)
Dataset Exercises
182(1)
Software Commands
182(2)
Answers to Self-Review
184(1)
Continuous Probability Distributions
185(26)
Introduction
186(1)
The Family of Uniform Distributions
186(3)
Exercises
189(1)
The Family of Normal Probability Distributions
190(3)
The Standard Normal Distribution
193(3)
The Empirical Rule
195(1)
Exercises
196(3)
Finding Areas under the Normal Curve
197(2)
Exercises
199(3)
Exercises
202(2)
Exercises
204(1)
Chapter Outline
204(1)
Chapter Exercises
205(3)
Dataset Exercises
208(1)
Software Commands
209(1)
Answers to Self-Review
210(1)
Sampling Methods and the Central Limit Theorem
211(34)
Introduction
212(1)
Sampling Methods
212(6)
Reasons to Sample
212(1)
Simple Random Sampling
213(3)
Systematic Random Sampling
216(1)
Stratified Random Sampling
216(1)
Cluster Sampling
217(1)
Exercises
218(4)
Sampling ``Error''
220(2)
Sampling Distribution of the Sample Mean
222(3)
Exercises
225(1)
The Central Limit Theorem
226(6)
Exercises
232(1)
Using the Sampling Distribution of the Sample Mean
233(4)
Exercises
237(1)
Chapter Outline
237(1)
Pronunciation Key
238(1)
Chapter Exercises
238(4)
exercises.com
242(1)
Dataset Exercises
243(1)
Software Commands
243(1)
Answers to Self-Review
244(1)
Estimation and Confidence Intervals
245(31)
Introduction
246(1)
Point Estimates and Confidence Intervals
246(7)
Known σ or a Large Sample
246(5)
A Computer Simulation
251(2)
Exercises
253(7)
Unknown Population Standard Deviation and a Small Sample
254(6)
Exercises
260(1)
A Confidence Interval for a Proportion
260(3)
Exercises
263(1)
Finite-Population Correction Factor
263(1)
Exercises
264(1)
Choosing an Appropriate Sample Size
265(2)
Exercises
267(1)
Chapter Outline
268(1)
Pronunciation Key
269(1)
Chapter Exercises
269(3)
exercises.com
272(1)
Dataset Exercises
273(1)
Software Commands
273(2)
Answers to Self-Review
275(1)
One-Sample Tests of Hypothesis
276(36)
Introduction
277(1)
What Is a Hypothesis?
277(1)
What Is Hypothesis Testing?
278(1)
Five-Step Procedure for Testing a Hypothesis
278(5)
Step 1: State the Null Hypothesis (Ho) and the Alternate Hypothesis (H1)
278(1)
Step 2: Select a Level of Significance
279(1)
Step 3: Select the Test Statistic
279(2)
Step 4: Formulate the Decision Rule
281(1)
Step 5: Make a Decision
282(1)
One-Tailed and Two-Tailed Tests of Significance
283(1)
Testing for a Population Mean with a Known Population Standard Deviation
284(4)
A Two-Tailed Test
284(4)
A One-Tailed Test
288(1)
p-Value in Hypothesis Testing
288(2)
Testing for a Population Mean: Large Sample, Population Standard Deviation Unknown
290(1)
Exercises
291(1)
Tests Concerning Proportions
292(3)
Exercises
295(1)
Testing for a Population Mean: Small Sample, Population Standard Deviation Unknown
295(5)
Exercises
300(3)
A Software Solution
301(2)
Exercises
303(1)
Chapter Outline
304(1)
Pronunciation Key
305(1)
Chapter Exercises
305(4)
exercises.com
309(1)
Dataset Exercises
309(1)
Software Commands
310(1)
Answers to Self-Review
311(1)
Two-Sample Tests of Hypothesis
312(32)
Introduction
313(1)
Two-Sample Tests of Hypothesis: Independent Samples
313(5)
Exercises
318(1)
Two-Sample Tests about Proportions
319(2)
Exercises
321(2)
Comparing Population Means with Small Samples
323(3)
Exercises
326(1)
Two-Sample Tests of Hypothesis: Dependent Samples
327(4)
Comparing Dependent and Independent Samples
331(2)
Exercises
333(1)
Chapter Outline
334(1)
Pronunciation Key
335(1)
Chapter Exercises
335(5)
exercises.com
340(1)
Dataset Exercises
341(1)
Software Commands
341(1)
Answers to Self-Review
342(2)
Analysis of Variance
344(30)
Introduction
345(1)
The F Distribution
345(1)
Comparing Two Population Variances
346(3)
Exercises
349(1)
Anova Assumptions
350(2)
The Anova Test
352(7)
Exercises
359(1)
Inferences about Pairs of Treatment Means
360(2)
Exercises
362(2)
Chapter Outline
364(1)
Pronunciation Key
365(1)
Chapter Exercises
365(5)
exercises.com
370(1)
Dataset Exercises
370(1)
Software Commands
371(2)
Answers to Self-Review
373(1)
Linear Regression and Correlation
374(47)
Introduction
375(1)
What Is Correlation Analysis?
375(2)
The Coefficient of Correlation
377(4)
The Coefficient of Determination
381(1)
Correlation and Cause
382(1)
Exercises
382(2)
Testing the Significance of the Correlation Coefficient
384(2)
Exercises
386(1)
Regression Analysis
386(4)
Least Squares Principle
386(3)
Drawing the Line of Regression
389(1)
Exercises
390(2)
The Standard Error of Estimate
392(3)
Assumptions Underlying Linear Regression
395(1)
Exercises
396(1)
Confidence and Prediction Intervals
396(4)
Exercises
400(1)
More on the Coefficient of Determination
400(3)
Exercises
403(1)
The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimate
403(2)
Transforming Data
405(2)
Exercises
407(1)
Chapter Outline
408(2)
Pronunciation Key
410(1)
Chapter Exercises
410(7)
exercises.com
417(1)
Dataset Exercises
417(1)
Software Commands
418(2)
Answers to Self-Review
420(1)
Multiple Regression and Correlation Analysis
421(43)
Introduction
422(1)
Multiple Regression Analysis
422(1)
Inferences in Multiple Linear Regression
423(3)
Exercises
426(2)
Multiple Standard Error of Estimate
428(1)
Assumptions about Multiple Regression and Correlation
429(1)
The Anova Table
430(2)
Exercises
432(1)
Evaluating the Regression Equation
432(9)
Using a Scatter Diagram
432(1)
Correlation Matrix
433(1)
Global Test: Testing the Multiple Regression Model
434(2)
Evaluating Individual Regression Coefficients
436(3)
Qualitative Independent Variables
439(2)
Exercises
441(1)
Analysis of Residuals
442(5)
Chapter Outline
447(1)
Pronunciation Key
448(1)
Chapter Exercises
448(11)
exercises.com
459(1)
Dataset Exercises
460(1)
Software Commands
461(2)
Answers to Self-Review
463(1)
Chi-Square Applications
464(61)
Introduction
464(1)
Goodness-of-Fit Test: Equal Expected Frequencies
465(5)
Exercises
470(1)
Goodness-of-Fit Test: Unequal Expected Frequencies
471(2)
Limitations of Chi-Square
473(2)
Exercises
475(271)
Contingency Table Analysis
746
Exercises
450(31)
Chapter Outline
481(1)
Pronunciation Key
481(1)
Chapter Exercises
482(2)
exercises.com
484(1)
Dataset Exercises
485(1)
Software Commands
486(1)
Answers to Self-Review
487(2)
Appendixes
Appendixes A--I Tables
Binomial Probability Distribution
489(5)
Critical Values of Chi-Square
494(1)
Poisson Distribution
495(1)
Areas under the Normal Curve
496(1)
Table of Random Numbers
497(1)
Student's t Distribution
498(1)
Critical Values of the F Distribution
499(2)
Wilcoxon T Values
501(1)
Factors for Control Charts
502(1)
Appendixes J--N Datasets
Real Estate
503(3)
Major League Baseball
506(2)
Wages and Wage Eamers
508(4)
CIA International Economic and Demographic Data
512(3)
Whitner Autoplex
515(1)
Appendix O Getting Started with Megastat
516(4)
Appendix P Visual Statistics
520(5)
Answers to Odd-Numbered Exercises 525(27)
Photo Credits 552(1)
Index 553


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