9780071461931

Statistics for the Utterly Confused, 2nd edition

by
  • ISBN13:

    9780071461931

  • ISBN10:

    0071461930

  • Edition: 2nd
  • Format: Paperback
  • Copyright: 2006-01-12
  • Publisher: McGraw-Hill Education

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Summary

Statistics for the Utterly Confused, Second Edition When it comes to understanding statistics, even good students can be confused. Perfect for students in any introductory non-calculus-based statistics course, and equally useful to professionals working in the world,Statistics for the Utterly Confusedis your ticket to success. Statistical concepts are explained step-by-step and applied to such diverse fields as business, economics, finance, and more. The message ofStatistics for the Utterly Confusedis simple: you don't have to be confused anymore. Updated and expanded to give you the latest changes in the field, this up-to-the-minute edition includes many new examples of Excel output, the most widely used of all statistics programs; a new chapter on Analysis of Variance (ANOVA); and 200 additions to the 700 self-testing questions and answers. The expert author's Web site also gives you tons of fresh examples, practice problems, and strategies--so you can go from utterly confused to totally prepared in no time! Inside, you'll discover how to: Grasp the meaning of everyday statistical concepts Find out what's probable and what isn't Read, understand, and solve statistics problems Improve your scores on exams Use your skills in any field

Author Biography

Lloyd R. Jaisingh, PhD, is Professor of Mathematics at Morehead State University, Morehead, Kentucky. He has published numerous books and articles on elementary statistics and technology in the classroom.

Table of Contents

Acknowledgments vi
Preface xiii
Technology Integration xiv
Organization of the Text xv
Part I DESCRIPTIVE STATISTICS
1(146)
Graphical Displays
3(28)
Do I Need to Read This Chapter?
3(1)
Introduction
4(2)
Frequency Distributions
6(5)
Dot Plots
11(1)
Bar Charts or Bar Graphs
12(1)
Histograms
13(2)
Frequency Polygons
15(1)
Stem-and-Leaf Displays or Plots
15(2)
Time-Series Graphs
17(1)
Pie Graphs or Pie Charts
17(1)
Pareto Charts
18(13)
Technology Corner
19(1)
It's a Wrap
19(1)
Test Yourself
19(12)
Numerical Measures of Central Tendency
31(20)
Do I Need to Read This Chapter?
31(1)
The Mean
32(2)
The Median
34(2)
The Mode
36(1)
Shapes (Skewness)
37(14)
Technology Corner
39(1)
It's a Wrap
40(1)
Test Yourself
40(11)
Numerical Measures of Variability
51(24)
Do I Need to Read This Chapter?
51(1)
The Range
52(1)
The Interquartile Range
53(1)
The Mean Absolute Deviation
54(2)
The Variance and Standard Deviation
56(3)
The Coefficient of Variation
59(1)
The Empirical Rule
60(2)
Skewness
62(13)
Technology Corner
63(1)
It's a Wrap
64(1)
Test Yourself
64(11)
Numerical Measures of Position
75(25)
Do I Need to Read This Chapter?
75(1)
The z Score or Standard Score
76(2)
Percentiles
78(4)
Box Plots
82(18)
Technology Corner
85(1)
It's a Wrap
86(1)
Test Yourself
86(14)
Exploring Bivariate Data
100(28)
Do I Need to Read This Chapter?
100(1)
Scatter Plots
101(1)
Looking for Patterns in the Data
102(2)
Correlation
104(3)
Correlation and Causation
107(1)
Least-Squares Regression Line
108(2)
The Coefficient of Determination
110(1)
Residual Plots
111(1)
Outliers and Influential Points
112(16)
Technology Corner
113(1)
It's a Wrap
114(1)
Test Yourself
114(14)
Exploring Categorical Data
128(19)
Do I Need to Read This Chapter?
128(1)
Marginal Distributions
129(1)
Conditional Distributions
130(2)
Using Bar Charts to Display Contingency Tables
132(2)
Independence in Categorical Variables
134(1)
Simpson's Paradox
135(12)
Technology Corner
138(1)
It's a Wrap
138(1)
Test Yourself
138(9)
Part II PROBABILITY
147(112)
Randomness, Uncertainty, and Probability
149(26)
Do I Need to Read This Chapter?
149(1)
Randomness and Uncertainty
150(1)
Random Experiments, Sample Space, and Events
150(1)
Classical Probability
151(2)
Relative Frequency or Empirical Probability
153(1)
The Law of Large Numbers
153(2)
Subjective Probability
155(1)
Some Basic Laws of Probability
155(1)
Other Probability Rules
156(5)
Conditional Probability
161(1)
Independence
162(13)
Technology Corner
163(1)
It's a Wrap
163(1)
Test Yourself
164(11)
Discrete Probability Distributions
175(28)
Do I Need to Read This Chapter?
175(1)
Random Variables
176(1)
Probability Distributions for Discrete Random Variables
177(2)
Expected Value for a Discrete Random Variable
179(3)
Variance and Standard Deviation of a Discrete Random Variable
182(3)
Bernoulli Trials and the Binomial Probability Distribution
185(18)
Technology Corner
189(1)
It's a Wrap
189(1)
Test Yourself
190(13)
The Normal Probability Distribution
203(26)
Do I Need to Read This Chapter?
203(1)
The Normal Probability Distribution
204(2)
Properties of the Normal Distribution
206(3)
The Standard Normal Distribution
209(5)
Applications of the Normal Distribution
214(15)
Technology Corner
216(1)
It's a Wrap
217(1)
Test Yourself
217(12)
Sampling Distributions and the Central Limit Theorem
229(30)
Do I Need to Read This Chapter?
229(1)
Sampling Distribution of a Sample Proportion
230(4)
Sampling Distribution of a Sample Mean
234(4)
Sampling Distribution of a Difference between Two Independent Sample Proportions
238(4)
Sampling Distribution of a Difference between Two Independent Sample Means
242(17)
Technology Corner
246(1)
It's a Wrap
246(1)
Test Yourself
246(13)
Part III STATISTICAL INFERENCE
259(140)
Confidence Intervals: Large Samples
261(26)
Do I Need to Read This Chapter?
261(1)
Large-Sample Confidence Interval for a Single Population Proportion
262(3)
Large-Sample Confidence Interval for a Single Population Mean
265(2)
Large-Sample Confidence Interval for the Difference between Two Population Proportions
267(1)
Large-Sample Confidence Interval for the Difference between Two Population Means
268(19)
Technology Corner
270(2)
It's a Wrap
272(1)
Test Yourself
272(15)
Hypothesis Tests: Large Samples
287(34)
Do I Need to Read This Chapter?
287(1)
Some Terms Associated with Hypothesis Testing
288(2)
Five-Step Process of Hypothesis Testing
290(1)
Large-Sample Test for a Population Proportion
290(5)
Large-Sample Test for a Population Mean
295(2)
Large-Sample Test for the Difference between Two Population Proportions
297(4)
Large-Sample Test for the Difference between Two Population Means
301(2)
P-Value Approach to Hypothesis Testing
303(18)
Technology Corner
306(2)
It's a Wrap
308(1)
Test Yourself
308(13)
Confidence Intervals and Hypothesis Tests: Small Samples
321(27)
Do I Need to Read This Chapter?
321(1)
The t Distribution
322(1)
Small-Sample Confidence Interval for a Population Mean
323(1)
Small-Sample Test for a Population Mean
324(3)
Independent Small-Sample Confidence Interval for the Difference between Two Population Means
327(2)
Independent Small-Sample Tests for the Difference between Two Population Means
329(2)
Dependent Small-Sample Confidence Interval for the Difference between Two Population Means
331(2)
Dependent Small-Sample Tests for the Difference between Two Population Means
333(15)
Technology Corner
335(1)
It's a Wrap
335(1)
Test Yourself
336(12)
Chi-Square Procedures
348(21)
Do I Need to Read This Chapter?
348(1)
The Chi-Square Distribution
348(2)
The Chi-Square Test for Goodness-of-Fit
350(5)
The Chi-Square Test for Independence
355(2)
Benford's Law
357(12)
Technology Corner
359(2)
It's a Wrap
361(1)
Test Yourself
361(8)
One-Way Analysis of Variance
369(30)
Do I Need to Read This Chapter?
369(1)
Comparing Population Means Graphically
370(3)
Some Terminology Associated with Analysis of Variance (ANOVA)
373(1)
The Hypothesis Test of One-Way Analysis of Variance
374(4)
The Test Statistic and the F Distribution
378(3)
One-Way or Single-Factor ANOVA Tests
381(18)
Technology Corner
384(2)
It's a Wrap
386(1)
Test Yourself
386(13)
Appendix 399(18)
Index 417

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