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Tables of Contents for Managerial Statistics
Chapter/Section Title
Page #
Page Count
Preface
xv
Introduction to Managerial Statistics
2
22
Introduction
4
2
An Overview of the Book
6
5
Excel versus Stand-alone Statistical Software
11
1
A Sampling of Examples
12
9
Conclusion
21
3
Case Study: Entertainment on a Cruise Ship
22
2
Describing Data: Graphs and Tables
24
48
Introduction
26
1
Basic Concepts
27
4
Frequency Tables and Histograms
31
11
Analyzing Relationships with Scatterplots
42
4
Time Series Plots
46
5
Exploring Data with Pivot Tables
51
9
Pivot Table Changes in Excel 2000
60
3
Conclusion
63
9
Case Study: Customer Arrivals at Bank98
70
1
Case Study: Automobile Production and Purchases
70
1
Case Study: Saving, Spending, and Social Climbing
71
1
Describing Data: Summary Measures
72
52
Introduction
74
1
Measures of Central Location
74
2
Quartiles and Percentiles
76
1
Minimum, Maximum, and Range
77
1
Measures of Variability: Variance and Standard Deviation
78
4
Obtaining Summary Measures with Add-Ins
82
5
Measures of Association: Covariance and Correlation
87
4
Describing Data Sets with Boxplots
91
4
Applying the Tools
95
17
Conclusion
112
12
Case Study: The Dow-Jones Averages
120
2
Case Study: Other Market Indexes
122
2
Getting the Right Data in Excel
124
54
Introduction
126
1
Cleaning the Data
127
9
Using Excel's AutoFilter
136
7
Complex Queries with the Advanced Filter
143
7
Importing External Data from Access
150
12
Creating Pivot Tables from External Data
162
3
Web Queries
165
10
Conclusion
175
3
Case Study: EduToys, Inc.
176
2
Probability and Probability Distributions
178
64
Introduction
180
1
Probability Essentials
181
6
Distribution of a Single Random Variable
187
4
An Introduction to Simulation
191
5
Subjective Versus Objective Probabilities
196
2
Derived Probability Distributions
198
4
Distribution of Two Random Variables: Scenario Approach
202
7
Distribution of Two Random Variables: Joint Probability Approach
209
10
Independent Random Variables
219
5
Weighted Sums of Random Variables
224
7
Conclusion
231
11
Case Study: Simpson's Paradox
240
2
Normal, Binomial, and Poisson Distributions
242
56
Introduction
244
1
The Normal Distribution
245
9
Applications of the Normal Distribution
254
12
The Binomial Distribution
266
4
Applications of the Binomial Distribution
270
12
The Poisson Distribution
282
4
Fitting a Probability Distribution to Data: BestFit
286
3
Conclusion
289
9
Case Study: EuroWatch Company
295
1
Case Study: Cashing in on the Lottery
296
2
Decision Making Under Uncertainty
298
78
Introduction
300
1
Elements of a Decision Analysis
301
11
The Precision Tree Add-In
312
10
Introduction to Influence Diagrams
322
6
More Single-Stage Examples
328
10
Multistage Decision Problems
338
9
Bayes' Rule
347
8
Incorporating Attitudes Toward Risk
355
8
Conclusion
363
13
Case Study: Jogger Shoe Company
374
1
Case Study: Westhouser Paper Company
374
2
Sampling and Sampling Distributions
376
46
Introduction
378
1
Sampling Terminology
378
1
Methods for Selecting Random Samples
379
16
An Introduction to Estimation
395
17
Conclusion
412
10
Case Study: Sampling from Videocassette Renters
421
1
Confidence Interval Estimation
422
64
Introduction
424
1
Sampling Distributions
425
4
Confidence Interval for a Mean
429
5
Confidence Interval for a Total
434
3
Confidence Interval for a Proporation
437
5
Confidence Interval for a Standard Deviation
442
4
Confidence Interval for the Difference Between Means
446
12
Confidence Interval for the Difference Between Proportions
458
8
Controlling Confidence Interval Length
466
7
Conclusion
473
13
Case Study: Harrigan University Admissions
480
1
Case Study: Employee Retention at D & Y
481
1
Case Study: Delivery Times at SnowPea Restaurant
482
1
Case Study: The Bodfish Lot Cruise
483
3
Hypothesis Testing
486
60
Introduction
488
1
Concepts in Hypothesis Testing
489
6
Hypothesis Tests for a Population Mean
495
10
Hypothesis Tests for Other Parameters
505
21
Tests for Normality
526
6
Chi-Square Test for Independence
532
5
Conclusion
537
9
Case Study: Regression Toward the Mean
542
1
Case Study: Baseball Statistics
543
1
Case Study: The Wichita Anti-Drunk Driving Advertising Campaign
543
3
Statistical Process Control
546
62
Introduction
549
1
Deming's 14 Points
550
3
Basic Ideas Behind Control Charts
553
2
Control Charts for Variables
555
20
Control Charts for Attributes
575
8
Process Capability
583
11
Conclusion
594
14
Case Study: The Lamination Process at Intergalactica
599
2
Case Study: Paper Production for Fornax at the Pluto Mill
601
7
Analysis of Variance and Experimental Design
608
46
Introduction
610
3
One-Way ANOVA
613
12
The Multiple Comparison Problem
625
6
Two-Way ANOVA
631
12
More About Experimental Design
643
9
Conclusion
652
2
Case Study: Krentz Appraisal Services
653
1
Regression Analysis: Estimating Relationships
654
68
Introduction
656
2
Scatterplots: Graphing Relationships
658
9
Correlations: Indicators of Linear Relationships
667
2
Simple Linear Regression
669
10
Multiple Regression
679
6
Modeling Possibilities
685
26
Validation of the Fit
711
2
Conclusion
713
9
Case Study: Quantity Discounts at the FirmChair Company
720
1
Case Study: Housing Price Structure in MidCity
720
1
Case Study: Demand for French Bread at Howie's
721
1
Case Study: Investing for Retirement
721
1
Regression Analysis: Statistical Inference
722
75
Introduction
724
1
The Statistical Model
725
3
Inferences About the Regression Coefficients
728
6
Multicollinearity
734
4
Include/Exclude Decisions
738
5
Stepwise Regression
743
5
A Test for the Overall Fit: The ANOVA Table
748
4
The Partial F Test
752
9
Outliers
761
6
Violations of Regression Assumptions
767
4
Prediction
771
8
Conclusion
779
18
Case Study: The Artsy Corporation
790
1
Case Study: Heating Oil at Dupree Fuels Company
791
2
Case Study: Developing a Flexible Budget at the Gunderson Plant
793
1
Case Study: Forecasting Overhead at Wagner Printers
794
3
Discriminant Analysis and Logistic Regression
797
39
Introduction
799
1
Discriminant Analysis
800
19
Logistic Regression
819
15
Choosing Between the Two Methods
834
1
Conclusion
834
2
Case Study: Understanding Cereal Brand Preferences
835
1
Time Series Analysis and Forecasting
836
70
Introduction
838
1
Forecasting Methods: An Overview
839
4
Random Series
843
10
The Random Walk Model
853
4
Autoregression Models
857
6
Regression-Based Trend Models
863
7
Moving Averages
870
6
Exponential Smoothing
876
14
Deseasonalizing: The Ratio-to-Moving-Averages Method
890
4
Estimating Seasonality with Regression
894
5
Econometric Models
899
1
Conclusion
900
6
Case Study: Arrivals at the Credit Union
904
1
Case Study: Forecasting Weekly Sales at Amanta
904
2
Statistical Reporting
906
20
Introduction
907
1
Suggestions for Good Statistical Report Writing
908
5
Examples of Statistical Reports
913
12
Conclusion
925
1
References
926
3
Index
929
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