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Statistics Unplugged

by
Edition:
4th
ISBN13:

9780840029430

ISBN10:
0840029438
Format:
Paperback
Pub. Date:
7/1/2012
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.

Table of Contents

Introduction: Methods, Material, and Moments to Rememberp. 1
The What and How of Statisticsp. 4
Before We Beginp. 5
A World of Informationp. 5
Levels of Measurementp. 8
Samples and Populationsp. 12
The Purposes of Statistical Analysisp. 14
Descriptive Statisticsp. 15
Inferential Statisticsp. 15
Chapter Summaryp. 17
Some Other Things You Should Knowp. 18
Key Termsp. 19
Chapter Problemsp. 19
Describing Data and Distributionsp. 21
Before We Beginp. 22
Measures of Central Tendencyp. 22
The Meanp. 22
The Medianp. 26
The Modep. 28
Measures of Variability or Dispersionp. 30
The Rangep. 30
Deviations From the Meanp. 31
The Mean Deviationp. 34
The Variancep. 36
The Standard Deviationp. 39
n Versus n-1p. 46
Chapter Summaryp. 50
Some Other Things You Should Knowp. 50
Key Termsp. 51
Chapter Problemsp. 51
The Shape of Distributionsp. 54
Before We Beginp. 55
The Basic Elementsp. 55
Beyond the Basics: Comparisons and Conclusionsp. 58
A Special Curvep. 63
Chapter Summaryp. 70
Some Other Things You Should Knowp. 71
Key Termsp. 72
Chapter Problemsp. 72
The Normal Curvep. 74
Before We Beginp. 75
Real-World Normal Curvesp. 76
Into the Theoretical Worldp. 79
The Table of Areas Under the Normal Curvep. 82
Finally, an Applicationp. 89
Chapter Summaryp. 93
Some Other Things You Should Knowp. 94
Key Termsp. 94
Chapter Problemsp. 95
Four Fundamental Conceptsp. 96
Before We Beginp. 97
Fundamental Concept #1: Random Samplingp. 97
Fundamental Concept #2: Sampling Errorp. 100
Fundamental Concept #3: The Sampling Distribution of Sample Meansp. 103
Fundamental Concept #4: The Central Limit Theoremp. 105
Chapter Summaryp. 110
Some Other Things You Should Knowp. 111
Key Termsp. 112
Chapter Problemsp. 112
Confidence Intervalsp. 114
Before We Beginp. 115
Confidence Interval for the Meanp. 115
Confidence Interval for the Mean With Knownp. 116
An Applicationp. 117
Reviewing Z Valuesp. 118
Z Values and the Width of the Intervalp. 120
Bringing in the Standard Error of the Meanp. 120
The Relevance of the Central Limit Theorem and the Standard Errorp. 123
Confidence and Interval Widthp. 126
A Brief Recapp. 128
Confidence Interval for the Mean With Unknownp. 129
Estimating the Standard Error of the Meanp. 129
The Family of t Distributionsp. 132
The Table for the Family of t Distributionsp. 134
An Applicationp. 138
A Final Comment About the Interpretation of a Confidence Interval for the Meanp. 140
A Final Comment About Z Versus tp. 141
Confidence Intervals for Proportionsp. 142
An Applicationp. 143
Margin of Errorp. 145
Chapter Summaryp. 147
Some Other Things You Should Knowp. 149
Key Termsp. 150
Chapter Problemsp. 150
Hypothesis Testing With a Single Sample Meanp. 155
Before We Beginp. 156
Setting the Stagep. 156
A Hypothesis as a Statement of Your Expectations: The Case of the Null Hypothesisp. 157
Single Sample Test With Knownp. 159
Refining the Null and Phrasing It the Right Wayp. 160
The Logic of the Testp. 161
Applying the Testp. 163
Levels of Significance, Critical Values, and the Critical Regionp. 166
But What If…p. 170
But What If We're Wrong?p. 171
Single Sample Test With Unknownp. 176
Applying the Testp. 177
Some Variations on a Themep. 178
Chapter Summaryp. 179
Some Other Things You Should Knowp. 180
Key Termsp. 181
Chapter Problemsp. 181
Hypothesis Testing With Two Samples (Mean Difference and Difference Between Means)p. 185
Before We Beginp. 186
Related Samplesp. 186
The Logic of the Testp. 187
The Null Hypothesisp. 191
Combining the Logic and the Nullp. 191
The Estimate of the Standard Error of the Mean Differencep. 192
Applying the Testp. 193
Interpreting the Resultsp. 193
Some Additional Examplesp. 194
Independent Samplesp. 195
The Logic of the Testp. 196
The Null Hypothesisp. 199
Combining the Logic and the Nullp. 199
The Estimate of the Standard Error of the Difference of Meansp. 199
Applying the Testp. 202
Interpreting the Resultsp. 202
Some Additional Examplesp. 203
Chapter Summaryp. 204
Some Other Things You Should Knowp. 205
Key Termsp. 206
Chapter Problemsp. 206
Beyond the Null Hypothesisp. 210
Before We Beginp. 211
Research or Alternative Hypothesesp. 211
One-Tailed and Two-Tailed Test Scenariosp. 213
Testing a Non-directional Research Hypothesisp. 214
Testing a Directional Research Hypothesisp. 217
Power and Effectp. 221
Chapter Summaryp. 225
Some Other Things You Should Knowp. 226
Key Termsp. 226
Chapter Problemsp. 227
Analysis of Variancep. 229
Before We Beginp. 231
The Logic of ANOVAp. 231
From Curves to Data Distributionsp. 233
The Different Meansp. 234
From Different Means to Different Types of Variationp. 236
The Null Hypothesisp. 238
The Applicationp. 239
Calculating the Within-Groups Sum of Squares (SSW)p. 240
Calculating the Between-Groups Sum of Squares (SSB)p. 243
From Sums of Squares to Estimates of Variancep. 245
Calculating the F Ratiop. 249
The Interpretationp. 250
Interpretation of the F Ratiop. 250
Post Hoc Testingp. 252
Chapter Summaryp. 256
Some Other Things You Should Knowp. 257
Key Termsp. 258
Chapter Problemsp. 258
The Chi-Square Testp. 263
Before We Beginp. 264
The Chi-Square Test of Independencep. 264
The Logic of the Testp. 265
A Focus on the Departure From Chancep. 269
The Null Hypothesisp. 270
The Applicationp. 271
The Formulap. 275
The Calculationp. 275
Conclusion and Interpretationp. 276
Chapter Summaryp. 278
Some Other Things You Should Knowp. 279
Key Termsp. 279
Chapter Problemsp. 280
Correlation and Regressionp. 283
Before We Beginp. 284
Scatter Plotsp. 284
Linear Associations: Direction and Strengthp. 286
Other Types of Associationp. 288
Correlation Analysisp. 289
Two Variables: X and Yp. 290
The Logic of Correlationp. 292
The Formula for Pearson's rp. 293
Applicationp. 296
Interpretationp. 298
An Additional Step: Testing the Nullp. 300
Conclusion and Interpretationp. 301
Regression Analysisp. 302
An Applicationp. 302
The Logic of Prediction and the Line of Best Fitp. 304
The Regression Equationp. 306
The Standard Error of the Estimatep. 309
Chapter Summaryp. 311
Some Other Things You Should Knowp. 311
Key Termsp. 312
Chapter Problemsp. 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 Analysisp. 328
It Usually Starts with Rows and Columnsp. 328
Good News; Words of Caution; It's Up to Youp. 332
Some of the More Common Formulas Used in the Textp. 334
Answers to Chapter Problemsp. 337
Glossaryp. 343
Referencesp. 349
Indexp. 351
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