Tuesday, December 30, 2008

Exploring or The Elements of Statistics with Applications to Economics and the Social Sciences

Exploring: Getting Started with Microsoft Office

Author: Robert Grauer

 

For Introductory Computer courses in Microsoft Office 2003 or courses in Computer Concepts with a lab component for Microsoft Office 2003 applications.


Master the How and Why of Office 2003!  Students master the "How and Why" of performing tasks in Office and gain a greater understanding of how to use the individual applications together to solve business problems.



Interesting textbook: More Natural Cures Revealed or A Tooth from the Tigers Mouth

The Elements of Statistics with Applications to Economics and the Social Sciences

Author: James B Ramsey

Designed for readers who want to stress the understanding of basic concepts and the development of "statistical intuition," this book demonstrates that statistical reasoning is everywhere and that statistical concepts are as important to readers' personal lives as they are to their future professional careers. Ramsey aims to develop statistically literacy—from the ability to read and think critically about statistics published in popular media to the ability to analyze and act upon statistics gathered in the business world. The underlying philosophy of this book is that given a reasonable level of depth in the analysis, the reader can later acquire a much more extensive, and even more intensive, exposure to statistics on their own or in the context of the work environment. Some use of calculus is included. Use of the computer is integrated throughout.

Booknews

Written for sophomore-level undergraduates, this textbook provides an introduction to statistics, especially as they are used in the social sciences. It explains fundamental ideas and principles, including descriptive statistics, probability, distribution, inference, bivariate distributions, regression, and ANOVA. Appendixes review basic mathematical concepts and conventions, offer directions for the student version of S-Plus 4.5, and provide supplementary information on nonparametric measures and Bayesian inference. Ramsey teaches at New York University. Annotation c. Book News, Inc., Portland, OR (booknews.com)



Table of Contents:
Prefacexiii
Part 1Introduction and Fundamental Ideas1
Chapter 1Statistics as Science2
1.1What You Will Learn in This Chapter2
1.2Introduction2
1.3Statistics: A Framework for Decision Making3
1.4Statistics and the Methodology of Science7
1.5Statistics as a Science9
The Subject Matter of Statistics9
Statistics and Science Interwined10
1.6Summary12
Case Study: Was There Age Discrimination in a Public Utility?13
1.7Addendum for the Reader14
Exercises17
Chapter 2Types of Variables, Measurements, and Explanation20
2.1What You Will Learn in This Chapter20
2.2Introduction20
2.3Types of Variables21
Cardinal Measurement23
Ordinal Measurement24
Categorical Variables25
Indices25
Time Series26
2.4Random and Deterministic Variables26
2.5Summary32
Case Study: Was There Age Discrimination in a Public Utility?32
Exercises33
Part 2Descriptive Statistics37
Chapter 3How to Describe and Summarize Random Data by Graphical Procedures38
3.1What You Will Learn in This Chapter38
3.2Introduction38
3.3Describing Data by Box-and-Whisker Plots40
The Median41
The Range43
Quartiles44
Box-and-Whisker Plots45
3.4Plotting Relative Frequencies48
3.5Cumulative Frequencies51
3.6Histogram53
3.7Summary63
Case Study: Was There Age Discrimination in a Public Utility?65
Exercises69
Chapter 4Moments and the Shape of Histograms77
4.1What You Will Learn in This Chapter77
4.2Introduction77
4.3The Mean, a Measure of Location77
An Aside on Notation79
Averaging Grouped Data81
Interpreting the Mean83
4.4The Second Moment as a Measure of Spread85
4.5General Definition of Moments88
The Third Moment as a Measure of Skewness90
The Fourth Moment as a Measure of Peakedness, or "Fat Tails"92
4.6Standardized Moments93
Some Practical Uses for Higher Moments99
4.7Standardization of Variables104
The Higher Moments about the Origin105
Higher Moments and Grouped Data106
4.8Summary106
Case Study: Was There Age Discrimination in a Public Utility?107
Exercises110
Chapter 5The Description of Bivariate Data120
5.1What You Will Learn in This Chapter120
5.2Introduction120
5.3Three-Dimensional Histograms121
5.4Scatter Plots122
5.5Standardization for Pairs of Random Variables125
5.6Covariation and m[subscript 11], the First Cross Product Moment126
5.7Linear Statistical Relationships and the Correlation Coefficient135
5.8The Correlation Coefficient and Slope140
5.9Rank Correlation142
5.10Bivariate Categorical Data144
Row Comparisons145
Column Comparisons147
Joint Comparisons148
5.11Summary152
Case Study: Was There Age Discrimination in a Public Utility?153
Exercises159
Part 3Probability and Distribution Theory169
Chapter 6The Theory of Statistics: An Introduction170
6.1What You Will Learn in This Chapter170
6.2Introduction171
6.3The Theory: First Steps173
The Sample Space173
Introducing Probabilities175
Probabilities of Unions and Joint Events177
A Mathematical Digression180
Calculating the Probabilities of the Union of Events182
The Definition of Probability for Sample Spaces of Discrete Events184
6.4Conditional Probability185
Summing Up the Many Definitions of Probability190
6.5Random Variables: Intuition Made Formal191
An Example Using Two Random Variables193
6.6Statistical Independence197
Application of the Results to Continuous Random Variables199
Consequences of the Equally Likely Principle200
6.7Summary202
Case Study: Was There Age Discrimination in a Public Utility?203
Excercises205
Chapter 7The Generation and Description of Discrete Probability Distributions214
7.1What You Will Learn in This Chapter214
7.2Introduction215
7.3Combinations and Permutations215
7.4Generating Binomial Probabilities220
The Convolution Sum222
Deriving the Binomial Distribution222
Parameters and the Shape of the Probability Distribution228
Theoretical Moments and the Shape of the Probability Distribution230
7.5Expectation236
Moment-Generating Functions for Discrete Variables242
7.6The Cumulative Distribution Function246
7.7The Poisson Probability Distribution246
7.8Summary253
Case Study: Was There Age Discrimination in a Public Utility?254
Exercises254
Chapter 8The Generation of Some Continuous Probability Distributions267
8.1What You Will Learn in This Chapter267
8.2Introduction267
8.3How to Express Probability in Terms of Continuous Random Variables268
8.4Theoretical Moments and Density Functions277
8.5The Uniform Distribution278
8.6The Normal, or Gaussian, Density Function and the Central Limit Theorem281
Standard Deviation and the Nonstandard Gaussian286
The Gaussian, or Normal, Distribution as an Approximation to the Binomial Distribution288
Moment-Generating Functions for Continuous Variables296
The Chebyshev Inequality299
Terminology301
8.7Summary302
Case Study: Was There Age Discrimination in a Public Utility?303
Exercises303
Part 4Basic Principles of Inference313
Chapter 9Elementary Sampling Theory314
9.1What You Will Learn in This Chapter314
9.2Introduction314
9.3An Illustrative Example316
9.4An Introduction to the Theory of Simple Random Sampling320
9.5Stratified Random Sampling325
9.6Summary329
Case Study: Was There Age Discrimination in a Public Utility?330
Exercises332
Chapter 10Estimation of Theoretical Moments and the Parameters of Probability Distributions337
10.1What You Will Learn in This Chapter337
10.2Introduction337
10.3Estimating Theoretical Moments: Large Sample Results339
10.4Estimating Moments and Parameters: Confidence Intervals and Small Sample Results347
Estimating a Binomial Probability356
Estimating the Poisson Parameter360
The Student's T Distribution363
The Chi-square Distribution and Confidence Intervals for the Variance372
10.5Maximum Likelihood Estimators375
10.6Summary379
Case Study: Was There Age Discrimination in a Public Utility?380
Exercises381
Chapter 11Hypothesis Testing: How to Discriminate between Two Alternatives393
11.1What You Will Learn in This Chapter393
11.2Introduction393
11.3The Basic Idea of Hypotheses Tests394
A Digression on the Interpretation of Rejection Regions399
How to Choose an Optimal Decision Rule399
Why Type I Error Is Usually Small407
The Special Rofe of the Null Hypothesis409
11.4Simple and Composite Hypotheses Tests411
11.5Two-Sided Hypotheses Tests415
11.6Tests of Proportions417
11.7Hypotheses Tests When the Variance Is Unknown418
Testing the Difference between Two Means421
An Aside on Statistical Significance425
P Values426
11.8Some Practical Examples428
11.9Summary433
Case Study: Was There Age Discrimination in a Public Utility?435
Exercises436
Part 5Bivariate Distributions, Regression, and ANOVA449
Chapter 12The Generation of Bivariate and Conditional Probability Distributions450
12.1What You Will Learn in This Chapter450
12.2Introduction450
12.3Some Pragmatic Examples454
12.4The Generation of a Bivariate Discrete Distribution457
12.5The Generation of a Bivariate Continuous Distribution458
The Conditional Normal Density Function468
Moments of Joint and Conditional Density Functions470
12.6Bivariate and Conditional Distributions Obtained by Sampling474
12.7Summary476
Case Study: Was There Age Discrimination in a Public Unility?476
Exercises477
Chapter 13The Theory and Practice of Regression Analysis481
13.1What You Will Learn in This Chapter481
13.2Introduction481
13.3The Regression Model483
13.4Estimation and Inference: The Basics489
The Coefficient of Determination and the Degree of Fit500
13.5Estimation and Inference: Confidence Intervals and Hypotheses Tests505
Confidence Intervals for the Regression Parameters506
Predicting the Dependent Variable508
Confidence Intervals for the Error Term Standard Deviation515
The F Distribution and Measuring the Goodness of Fit516
Testing Hypotheses in Regression Equations520
Calculations522
13.6The "Regression" in Regression Analysis524
13.7Summary527
Case Study: Was There Age Discrimination in a Public Utility?528
Exercises531
Chapter 14Comparing Populations through the Analysis of Variance541
14.1What You Will Learn in This Chapter541
14.2Introduction541
14.3An Introduction to One-Way Analysis of Variance543
For Multiple Treatments, Which Is Best?550
The Link to Regression Analysis555
14.4Summary558
Case Study: Was There Age Discrimination in a Public Utility?559
Exercises561
Part 6Retrospective567
Chapter 15Retrospective568
15.1What You Will Learn in This Chapter568
15.2Introduction568
15.3A Schematic Review of What You Have Learned568
15.4The Role of Statistics in Everyday Life572
Case Study: Was There Age Discrimination in a Public Utility?574
15.5The Relationship between Science and Statistics575
15.6What Might You Learn Next in Statistics?576
Exercises577
Part 7Appendixes581
Appendix AMathematical Appendix: Review of Concepts and Conventions582
A.1Notational Conventions583
A.2Indexing586
A.3Sigma Notation587
A.4Elementary Set Theory593
A.5Elements of Calculus596
Exercises616
Appendix BDirections for Using the Student Version of S-Plus 4.5620
B.1Installing, Starting, and Closing S-Plus620
B.2Using S-Plus in This Text621
B.3General Notes about S-Plus621
B.4Data Files622
B.5Windows in S-Plus622
B.6Menu Bar Commands624
B.7Probability and Density Calculations628
B.8Statistical Tables636
Supplemental Material
Supplement CNonparametric Measures
Supplement DBayesian Inference
Index643

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