Statistics Unplugged

by Caldwell, Sally

Edition: 4th

ISBN13: 9780840029430

ISBN10: 0840029438

Format: Paperback

Pub. Date: 2012-07-24

Publisher(s): Cengage Learning

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Summary

Learn statistics the easy way with STATISTICS UNPLUGGED! Written in a friendly, easy-to-understand style, this practical book takes the intimidation out of statistics and helps you understand the relevance of statistics to your own life. Interesting examples throughout the book allow you to see what is really going on with the numbers instead of being overwhelmed by the numbers themselves.

Introduction: Methods, Material, and Moments to Remember	p. 1
The What and How of Statistics	p. 4
Before We Begin	p. 5
A World of Information	p. 5
Levels of Measurement	p. 8
Samples and Populations	p. 12
The Purposes of Statistical Analysis	p. 14
Descriptive Statistics	p. 15
Inferential Statistics	p. 15
Chapter Summary	p. 17
Some Other Things You Should Know	p. 18
Key Terms	p. 19
Chapter Problems	p. 19
Describing Data and Distributions	p. 21
Before We Begin	p. 22
Measures of Central Tendency	p. 22
The Mean	p. 22
The Median	p. 26
The Mode	p. 28
Measures of Variability or Dispersion	p. 30
The Range	p. 30
Deviations From the Mean	p. 31
The Mean Deviation	p. 34
The Variance	p. 36
The Standard Deviation	p. 39
n Versus n-1	p. 46
Chapter Summary	p. 50
Some Other Things You Should Know	p. 50
Key Terms	p. 51
Chapter Problems	p. 51
The Shape of Distributions	p. 54
Before We Begin	p. 55
The Basic Elements	p. 55
Beyond the Basics: Comparisons and Conclusions	p. 58
A Special Curve	p. 63
Chapter Summary	p. 70
Some Other Things You Should Know	p. 71
Key Terms	p. 72
Chapter Problems	p. 72
The Normal Curve	p. 74
Before We Begin	p. 75
Real-World Normal Curves	p. 76
Into the Theoretical World	p. 79
The Table of Areas Under the Normal Curve	p. 82
Finally, an Application	p. 89
Chapter Summary	p. 93
Some Other Things You Should Know	p. 94
Key Terms	p. 94
Chapter Problems	p. 95
Four Fundamental Concepts	p. 96
Before We Begin	p. 97
Fundamental Concept #1: Random Sampling	p. 97
Fundamental Concept #2: Sampling Error	p. 100
Fundamental Concept #3: The Sampling Distribution of Sample Means	p. 103
Fundamental Concept #4: The Central Limit Theorem	p. 105
Chapter Summary	p. 110
Some Other Things You Should Know	p. 111
Key Terms	p. 112
Chapter Problems	p. 112
Confidence Intervals	p. 114
Before We Begin	p. 115
Confidence Interval for the Mean	p. 115
Confidence Interval for the Mean With ¿ Known	p. 116
An Application	p. 117
Reviewing Z Values	p. 118
Z Values and the Width of the Interval	p. 120
Bringing in the Standard Error of the Mean	p. 120
The Relevance of the Central Limit Theorem and the Standard Error	p. 123
Confidence and Interval Width	p. 126
A Brief Recap	p. 128
Confidence Interval for the Mean With ¿ Unknown	p. 129
Estimating the Standard Error of the Mean	p. 129
The Family of t Distributions	p. 132
The Table for the Family of t Distributions	p. 134
An Application	p. 138
A Final Comment About the Interpretation of a Confidence Interval for the Mean	p. 140
A Final Comment About Z Versus t	p. 141
Confidence Intervals for Proportions	p. 142
An Application	p. 143
Margin of Error	p. 145
Chapter Summary	p. 147
Some Other Things You Should Know	p. 149
Key Terms	p. 150
Chapter Problems	p. 150
Hypothesis Testing With a Single Sample Mean	p. 155
Before We Begin	p. 156
Setting the Stage	p. 156
A Hypothesis as a Statement of Your Expectations: The Case of the Null Hypothesis	p. 157
Single Sample Test With ¿ Known	p. 159
Refining the Null and Phrasing It the Right Way	p. 160
The Logic of the Test	p. 161
Applying the Test	p. 163
Levels of Significance, Critical Values, and the Critical Region	p. 166
But What If…	p. 170
But What If We're Wrong?	p. 171
Single Sample Test With ¿ Unknown	p. 176
Applying the Test	p. 177
Some Variations on a Theme	p. 178
Chapter Summary	p. 179
Some Other Things You Should Know	p. 180
Key Terms	p. 181
Chapter Problems	p. 181
Hypothesis Testing With Two Samples (Mean Difference and Difference Between Means)	p. 185
Before We Begin	p. 186
Related Samples	p. 186
The Logic of the Test	p. 187
The Null Hypothesis	p. 191
Combining the Logic and the Null	p. 191
The Estimate of the Standard Error of the Mean Difference	p. 192
Applying the Test	p. 193
Interpreting the Results	p. 193
Some Additional Examples	p. 194
Independent Samples	p. 195
The Logic of the Test	p. 196
The Null Hypothesis	p. 199
Combining the Logic and the Null	p. 199
The Estimate of the Standard Error of the Difference of Means	p. 199
Applying the Test	p. 202
Interpreting the Results	p. 202
Some Additional Examples	p. 203
Chapter Summary	p. 204
Some Other Things You Should Know	p. 205
Key Terms	p. 206
Chapter Problems	p. 206
Beyond the Null Hypothesis	p. 210
Before We Begin	p. 211
Research or Alternative Hypotheses	p. 211
One-Tailed and Two-Tailed Test Scenarios	p. 213
Testing a Non-directional Research Hypothesis	p. 214
Testing a Directional Research Hypothesis	p. 217
Power and Effect	p. 221
Chapter Summary	p. 225
Some Other Things You Should Know	p. 226
Key Terms	p. 226
Chapter Problems	p. 227
Analysis of Variance	p. 229
Before We Begin	p. 231
The Logic of ANOVA	p. 231
From Curves to Data Distributions	p. 233
The Different Means	p. 234
From Different Means to Different Types of Variation	p. 236
The Null Hypothesis	p. 238
The Application	p. 239
Calculating the Within-Groups Sum of Squares (SS_W)	p. 240
Calculating the Between-Groups Sum of Squares (SS_B)	p. 243
From Sums of Squares to Estimates of Variance	p. 245
Calculating the F Ratio	p. 249
The Interpretation	p. 250
Interpretation of the F Ratio	p. 250
Post Hoc Testing	p. 252
Chapter Summary	p. 256
Some Other Things You Should Know	p. 257
Key Terms	p. 258
Chapter Problems	p. 258
The Chi-Square Test	p. 263
Before We Begin	p. 264
The Chi-Square Test of Independence	p. 264
The Logic of the Test	p. 265
A Focus on the Departure From Chance	p. 269
The Null Hypothesis	p. 270
The Application	p. 271
The Formula	p. 275
The Calculation	p. 275
Conclusion and Interpretation	p. 276
Chapter Summary	p. 278
Some Other Things You Should Know	p. 279
Key Terms	p. 279
Chapter Problems	p. 280
Correlation and Regression	p. 283
Before We Begin	p. 284
Scatter Plots	p. 284
Linear Associations: Direction and Strength	p. 286
Other Types of Association	p. 288
Correlation Analysis	p. 289
Two Variables: X and Y	p. 290
The Logic of Correlation	p. 292
The Formula for Pearson's r	p. 293
Application	p. 296
Interpretation	p. 298
An Additional Step: Testing the Null	p. 300
Conclusion and Interpretation	p. 301
Regression Analysis	p. 302
An Application	p. 302
The Logic of Prediction and the Line of Best Fit	p. 304
The Regression Equation	p. 306
The Standard Error of the Estimate	p. 309
Chapter Summary	p. 311
Some Other Things You Should Know	p. 311
Key Terms	p. 312
Chapter Problems	p. 313
Table of Areas Under the Normal Curve (Distribution of Z)	p. 318
Family of t Distributions (Two-Tailed Test)	p. 320
Family of t Distributions (One-Tailed Test)	p. 321
Distribution of F (.05 Level of Significance)	p. 322
Distribution of F (.01 Level of Significance)	p. 323
Distribution of Q (.05 Level of Significance)	p. 324
Distribution of Q (.01 Level of Significance)	p. 325
Critical Values for Chi-Square (X²)	p. 326
Critical Values of r (Correlation Coefficient)	p. 327
Data Sets and Computer-Based Data Analysis	p. 328
It Usually Starts with Rows and Columns	p. 328
Good News; Words of Caution; It's Up to You	p. 332
Some of the More Common Formulas Used in the Text	p. 334
Answers to Chapter Problems	p. 337
Glossary	p. 343
References	p. 349
Index	p. 351
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