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Solution Manual for Introduction to Business Statistics, 7th Edition

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Solution Manual for Introduction to Business Statistics, 7th Edition

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ISBN-10 ‏ : ‎ 053845217X
ISBN-13 ‏ : ‎ 978-0538452175
Author: Dr. Ron Weiers

Highly praised for its exceptional clarity, technical accuracy, and useful examples, Weiers’ INTRODUCTION TO BUSINESS STATISTICS, Seventh Edition, introduces fundamental statistical concepts with an engaging, conversational presentation and a strong emphasis on the practical relevance of course material to students’ lives and careers. The text’s outstanding illustrations, friendly language, non-technical terminology, and current examples involving real-world business and personal settings will capture students’ interest and prepare them for success from day one. Continuing cases, contemporary business applications, and more than 300 new or revised exercises and problems reflect important trends and the latest developments in today’s dynamic business environment — all with an accuracy you and your students can trust.

Table contents:

CHAPTER 1: A Preview of Business Statistics
1.1: INTRODUCTION
1.2: STATISTICS: YESTERDAY AND TODAY
1.3: DESCRIPTIVE VERSUS INFERENTIAL STATISTICS
1.4: TYPES OF VARIABLES AND SCALES OF MEASUREMENT
1.5: STATISTICS IN BUSINESS DECISIONS
1.6: BUSINESS STATISTICS: TOOLS VERSUS TRICKS
1.7: SUMMARY
STATISTICS IN ACTION
CHAPTER EXERCISES
CHAPTER 2: Visual Description of Data
2.1: INTRODUCTION
2.2: THE FREQUENCY DISTRIBUTION AND THE HISTOGRAM
2.3: THE STEM-AND-LEAF DISPLAY AND THE DOTPLOT
2.4: OTHER METHODS FOR VISUAL REPRESENTATION OF THE DATA
2.5: THE SCATTER DIAGRAM
2.6: TABULATION, CONTINGENCY TABLES, AND THE EXCEL PivotTable
2.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
CHAPTER 3: Statistical Description of Data
3.1: INTRODUCTION
3.2: STATISTICAL DESCRIPTION: MEASURES OF CENTRAL TENDENCY
3.3: STATISTICAL DESCRIPTION: MEASURES OF DISPERSION
3.4: ADDITIONAL DISPERSION TOPICS
3.5: DESCRIPTIVE STATISTICS FROM GROUPED DATA
3.6: STATISTICAL MEASURES OF ASSOCIATION
3.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
SEEING STATISTICS: APPLET 1
SEEING STATISTICS: APPLET 2
CHAPTER 4: Data Collection and Sampling Methods
4.1: INTRODUCTION
4.2: RESEARCH BASICS
4.3: SURVEY RESEARCH
4.4: EXPERIMENTATION AND OBSERVATIONAL RESEARCH
4.5: SECONDARY DATA
4.6: THE BASICS OF SAMPLING
4.7: SAMPLING METHODS
4.8: SUMMARY
CHAPTER EXERCISES
INTEGRATED CASE
SEEING STATISTICS: APPLET 3
CHAPTER 5: Probability: Review of Basic Concepts
5.1: INTRODUCTION
5.2: PROBABILITY: TERMS AND APPROACHES
5.3: UNIONS AND INTERSECTIONS OF EVENTS
5.4: ADDITION RULES FOR PROBABILITY
5.5: MULTIPLICATION RULES FOR PROBABILITY
5.6: BAYES’ THEOREM AND THE REVISION OF PROBABILITIES
5.7: COUNTING: PERMUTATIONS AND COMBINATIONS
5.8: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
CHAPTER 6: Discrete Probability Distributions
6.1: INTRODUCTION
6.2: THE BINOMIAL DISTRIBUTION
6.3: THE HYPERGEOMETRIC DISTRIBUTION
6.4: THE POISSON DISTRIBUTION
6.5: SIMULATING OBSERVATIONS FROM A DISCRETE PROBABILITY DISTRIBUTION
6.6: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASE
CHAPTER 7: Continuous Probability Distributions
7.1: INTRODUCTION
7.2: THE NORMAL DISTRIBUTION
7.3: THE STANDARD NORMAL DISTRIBUTION
7.4: THE NORMAL APPROXIMATION TO THE BINOMIAL DISTRIBUTION
7.5: THE EXPONENTIAL DISTRIBUTION
7.6: SIMULATING OBSERVATIONS FROM A CONTINUOUS PROBABILITY DISTRIBUTION
7.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
SEEING STATISTICS: APPLET 4
SEEING STATISTICS: APPLET 5
SEEING STATISTICS: APPLET 6
CHAPTER 8: Sampling Distributions
8.1: INTRODUCTION
8.2: A PREVIEW OF SAMPLING DISTRIBUTIONS
8.3: THE SAMPLING DISTRIBUTION OF THE MEAN
8.4: THE SAMPLING DISTRIBUTION OF THE PROPORTION
8.5: SAMPLING DISTRIBUTIONS WHEN THE POPULATION IS FINITE
8.6: COMPUTER SIMULATION OF SAMPLING DISTRIBUTIONS
8.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASE
SEEING STATISTICS: APPLET 7
SEEING STATISTICS: APPLET 8
CHAPTER 9: Estimation from Sample Data
9.1: INTRODUCTION
9.2: POINT ESTIMATES
9.3: A PREVIEW OF INTERVAL ESTIMATES
9.4: CONFIDENCE INTERVAL ESTIMATES FOR THE MEAN: σ KNOWN
9.5: CONFIDENCE INTERVAL ESTIMATES FOR THE MEAN: σ UNKNOWN
9.6: CONFIDENCE INTERVAL ESTIMATES FOR THE POPULATION PROPORTION
9.7: SAMPLE SIZE DETERMINATION
9.8: WHEN THE POPULATION IS FINITE
9.9: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
SEEING STATISTICS: APPLET 9
SEEING STATISTICS: APPLET 10
SEEING STATISTICS: APPLET 11
CHAPTER 10: Hypothesis Tests Involving a Sample Mean or Proportion
10.1: INTRODUCTION
10.2: HYPOTHESIS TESTING: BASIC PROCEDURES
10.3: TESTING A MEAN, POPULATION STANDARD DEVIATION KNOWN
10.4: CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
10.5: TESTING A MEAN, POPULATION STANDARD DEVIATION UNKNOWN
10.6: TESTING A PROPORTION
10.7: THE POWER OF A HYPOTHESIS TEST
10.8: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
SEEING STATISTICS: APPLET 12
SEEING STATISTICS: APPLET 13
CHAPTER 11: Hypothesis Tests Involving Two Sample Means or Proportions
11.1: INTRODUCTION
11.2: THE POOLED-VARIANCES t-TEST FOR COMPARING THE MEANS OF TWO INDEPENDENT SAMPLES
11.3: THE UNEQUAL-VARIANCES t-TEST FOR COMPARING THE MEANS OF TWO INDEPENDENT SAMPLES
11.4: THE z-TEST FOR COMPARING THE MEANS OF TWO INDEPENDENT SAMPLES
11.5: COMPARING TWO MEANS WHEN THE SAMPLES ARE DEPENDENT
11.6: COMPARING TWO SAMPLE PROPORTIONS
11.7: COMPARING THE VARIANCES OF TWO INDEPENDENT SAMPLES
11.8: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
SEEING STATISTICS: APPLET 14
CHAPTER 12: Analysis of Variance Tests
12.1: INTRODUCTION
12.2: ANALYSIS OF VARIANCE: BASIC CONCEPTS
12.3: ONE-WAY ANALYSIS OF VARIANCE
12.4: THE RANDOMIZED BLOCK DESIGN
12.5: TWO-WAY ANALYSIS OF VARIANCE
12.6: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
SEEING STATISTICS: APPLET 15
SEEING STATISTICS: APPLET 16
CHAPTER 13: Chi-Square Applications
13.1: INTRODUCTION
13.2: BASIC CONCEPTS IN CHI-SQUARE TESTING
13.3: TESTS FOR GOODNESS OF FIT AND NORMALITY
13.4: TESTING THE INDEPENDENCE OF TWO VARIABLES
13.5: COMPARING PROPORTIONS FROM k INDEPENDENT SAMPLES
13.6: ESTIMATION AND TESTS REGARDING THE POPULATION VARIANCE
13.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
SEEING STATISTICS: APPLET 17
CHAPTER 14: Nonparametric Methods
14.1: INTRODUCTION
14.2: WILCOXON SIGNED RANK TEST FOR ONE SAMPLE
14.3: WILCOXON SIGNED RANK TEST FOR COMPARING PAIRED SAMPLES
14.4: WILCOXON RANK SUM TEST FOR COMPARING TWO INDEPENDENT SAMPLES
14.5: KRUSKAL-WALLIS TEST FOR COMPARING MORE THAN TWO INDEPENDENT SAMPLES
14.6: FRIEDMAN TEST FOR THE RANDOMIZED BLOCK DESIGN
14.7: OTHER NONPARAMETRIC METHODS
14.8: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASE
BUSINESS CASE
CHAPTER 15: Simple Linear Regression and Correlation
15.1: INTRODUCTION
15.2: THE SIMPLE LINEAR REGRESSION MODEL
15.3: INTERVAL ESTIMATION USING THE SAMPLE REGRESSION LINE
15.4: CORRELATION ANALYSIS
15.5: ESTIMATION AND TESTS REGARDING THE SAMPLE REGRESSION LINE
15.6: ADDITIONAL TOPICS IN REGRESSION AND CORRELATION ANALYSIS
15.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
SEEING STATISTICS: APPLET 18
SEEING STATISTICS: APPLET 19
SEEING STATISTICS: APPLET 20
CHAPTER 16: Multiple Regression and Correlation
16.1: INTRODUCTION
16.2: THE MULTIPLE REGRESSION MODEL
16.3: INTERVAL ESTIMATION IN MULTIPLE REGRESSION
16.4: MULTIPLE CORRELATION ANALYSIS
16.5: SIGNIFICANCE TESTS IN MULTIPLE REGRESSION AND CORRELATION
16.6: OVERVIEW OF THE COMPUTER ANALYSIS AND INTERPRETATION
16.7: ADDITIONAL TOPICS IN MULTIPLE REGRESSION AND CORRELATION
16.8: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
CHAPTER 17: Model Building
17.1: INTRODUCTION
17.2: POLYNOMIAL MODELS WITH ONE QUANTITATIVE PREDICTOR VARIABLE
17.3: POLYNOMIAL MODELS WITH TWO QUANTITATIVE PREDICTOR VARIABLES
17.4: QUALITATIVE VARIABLES
17.5: DATA TRANSFORMATIONS
17.6: MULTICOLLINEARITY
17.7: STEPWISE REGRESSION
17.8: SELECTING A MODEL
17.9: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
BUSINESS CASE
CHAPTER 18: Models for Time Series and Forecasting
18.1: INTRODUCTION
18.2: TIME SERIES
18.3: SMOOTHING TECHNIQUES
18.4: SEASONAL INDEXES
18.5: FORECASTING
18.6: EVALUATING ALTERNATIVE MODELS: MAD AND MSE
18.7: AUTOCORRELATION, THE DURBIN-WATSON TEST, AND AUTOREGRESSIVE FORECASTING
18.8: INDEX NUMBERS
18.9: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASE
CHAPTER 19: Decision Theory
19.1: INTRODUCTION
19.2: STRUCTURING THE DECISION SITUATION
19.3: NON-BAYESIAN DECISION MAKING
19.4: BAYESIAN DECISION MAKING
19.5: THE OPPORTUNITY LOSS APPROACH
19.6: INCREMENTAL ANALYSIS AND INVENTORY DECISIONS
19.7: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASE
CHAPTER 20: Total Quality Management
20.1: INTRODUCTION
20.2: A HISTORICAL PERSPECTIVE AND DEFECT DETECTION
20.3: THE EMERGENCE OF TOTAL QUALITY MANAGEMENT
20.4: PRACTICING TOTAL QUALITY MANAGEMENT
20.5: SOME STATISTICAL TOOLS FOR TOTAL QUALITY MANAGEMENT
20.6: STATISTICAL PROCESS CONTROL: THE CONCEPTS
20.7: CONTROL CHARTS FOR VARIABLES
20.8: CONTROL CHARTS FOR ATTRIBUTES
20.9: ADDITIONAL STATISTICAL PROCESS CONTROL AND QUALITY MANAGEMENT TOPICS
20.10: SUMMARY
EQUATIONS
CHAPTER EXERCISES
INTEGRATED CASES
SEEING STATISTICS: APPLET 21
APPENDIX A: STATISTICAL TABLES
APPENDIX B: SELECTED ANSWERS
INDEX/GLOSSARY

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