Theory and Problems of Beginning Statistics

Name: Theory and Problems of Beginning Statistics
Price: 5.02 USD
Availability: InStock
ISBN: 9780071459327

ISBN-10: 0071459324

ISBN-13: 9780071459327

Edition: 2nd 2006 (Revised)

Authors: Larry J. Stephens

List price: $18.95

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Description:

Larry Stephens explains basic statistical concepts for students on introductory statistics courses. Concepts have been simplified to make this text accessible to students who need to study statistics as part of their social science or business course.

Book details

List price: $18.95
Edition: 2nd
Copyright year: 2006
Publisher: McGraw-Hill Companies, The
Binding: Paperback
Pages: 416
Size: 8.00" wide x 10.50" long x 0.50" tall
Weight: 1.584
Language: English

Larry Stephens, Ph.D., (Omaha, NE) is Professor of Mathematics at the University of Nebraska and is also the author of several books.

Introduction	p. 1
Statistics	p. 1
Descriptive Statistics	p. 1
Inferential Statistics: Population and Sample	p. 1
Variable, Observation, and Data Set	p. 2
Quantitative Variable: Discrete and Continuous Variable	p. 3
Qualitative Variable	p. 4
Nominal, Ordinal, Interval, and Ratio Levels of Measurement	p. 5
Summation Notation	p. 6
Computer Software and Statistics	p. 8
Organizing Data	p. 16
Raw Data	p. 16
Frequency Distribution for Qualitative Data	p. 16
Relative Frequency of a Category	p. 17
Percentage	p. 17
Bar Graph	p. 17
Pie Chart	p. 18
Frequency Distribution for Quantitative Data	p. 19
Class Limits, Class Boundaries, Class Marks, and Class Width	p. 20
Single-Valued Classes	p. 21
Histograms	p. 22
Cumulative Frequency Distributions	p. 24
Cumulative Relative Frequency Distributions	p. 24
Ogives	p. 24
Stem-and-Leaf Displays	p. 25
Descriptive Measures	p. 46
Measures of Central Tendency	p. 46
Mean, Median, and Mode for Ungrouped Data	p. 46
Measures of Dispersion	p. 48
Range, Variance, and Standard Deviation for Ungrouped Data	p. 49
Measures of Central Tendency and Dispersion for Grouped Data	p. 51
Chebyshev's Theorem	p. 52
Empirical Rule	p. 53
Coefficient of Variation	p. 53
Z Scores	p. 53
Measures of Position: Percentiles, Deciles, and Quartiles	p. 54
Interquartile Range	p. 56
Box-and-Whisker Plot	p. 56
Probability	p. 71
Experiment, Outcomes, and Sample Space	p. 71
Tree Diagrams and the Counting Rule	p. 71
Events, Simple Events, and Compound Events	p. 73
Probability	p. 73
Classical, Relative Frequency and Subjective Probability Definitions	p. 74
Marginal and Conditional Probabilities	p. 76
Mutually Exclusive Events	p. 77
Dependent and Independent Events	p. 78
Complementary Events	p. 79
Multiplication Rule for the Intersection of Events	p. 79
Addition Rule for the Union of Events	p. 80
Bayes' Theorem	p. 81
Permutations and Combinations	p. 82
Using Permutations and Combinations to Solve Probability Problems	p. 83
Discrete Random Variables	p. 98
Random Variable	p. 98
Discrete Random Variable	p. 98
Continuous Random Variable	p. 99
Probability Distribution	p. 99
Mean of a Discrete Random Variable	p. 100
Standard Deviation of a Discrete Random Variable	p. 101
Binomial Random Variable	p. 102
Binomial Probability Formula	p. 103
Tables of the Binomial Distribution	p. 105
Mean and Standard Deviation of a Binomial Random Variable	p. 106
Poisson Random Variable	p. 106
Poisson Probability Formula	p. 107
Hypergeometric Random Variable	p. 108
Hypergeometric Probability Formula	p. 109
Continuous Random Variables and Their Probability Distributions	p. 124
Uniform Probability Distribution	p. 124
Mean and Standard Deviation for the Uniform Probability Distribution	p. 125
Normal Probability Distribution	p. 126
Standard Normal Distribution	p. 128
Standardizing a Normal Distribution	p. 132
Applications of the Normal Distribution	p. 132
Determining the z and x Values When an Area under the Normal Curve is Known	p. 135
Normal Approximation to the Binomial Distribution	p. 137
Exponential Probability Distribution	p. 139
Probabilities for the Exponential Probability Distribution	p. 140
Sampling Distributions	p. 152
Simple Random Sampling	p. 152
Using Random Number Tables	p. 152
Using the Computer to Obtain a Simple Random Sample	p. 153
Systematic Random Sampling	p. 154
Cluster Sampling	p. 154
Stratified Sampling	p. 154
Sampling Distribution of the Sampling Mean	p. 154
Sampling Error	p. 156
Mean and Standard Deviation of the Sample Mean	p. 156
Shape of the Sampling Distribution of the Sample Mean and the Central Limit Theorem	p. 158
Applications of the Sampling Distribution of the Sample Mean	p. 158
Sampling Distribution of the Sample Proportion	p. 160
Mean and Standard Deviation of the Sample Proportion	p. 161
Shape of the Sampling Distribution of the Sample Proportion and the Central Limit Theorem	p. 162
Applications of the Sampling Distribution of the Sample Proportion	p. 163
Estimation and Sample Size Determination: One Population	p. 179
Point Estimate	p. 179
Interval Estimate	p. 179
Confidence Interval for the Population Mean: Large Samples	p. 179
Maximum Error of Estimate for the Population Mean	p. 181
The t Distribution	p. 182
Confidence Interval for the Population Mean: Small Samples	p. 184
Confidence Interval for the Population Proportion: Large Samples	p. 187
Determining the Sample Size for the Estimation of the Population Mean	p. 188
Determining the Sample Size for the Estimation of the Population Proportion	p. 189
Tests of Hypotheses: One Population	p. 200
Null Hypothesis and Alternative Hypothesis	p. 200
Test Statistic, Critical Values, Rejection and Nonrejection Regions	p. 201
Type I and Type II Errors	p. 202
Hypothesis Tests about a Population Mean: Large Samples	p. 207
Calculating Type II Errors	p. 209
P Values	p. 212
Hypothesis Tests about a Population Mean: Small Samples	p. 215
Hypothesis Tests about a Population Proportion: Large Samples	p. 217
Inferences for Two Populations	p. 229
Sampling Distribution of X[subscript 1] - X[subscript 2] for Large Independent Samples	p. 229
Estimation of [mu subscript 1] - [mu subscript 2] Using Large Independent Samples	p. 230
Testing Hypothesis about [mu subscript 1] - [mu subscript 2] Using Large Independent Samples	p. 232
Sampling Distribution of X[subscript 1] - X[subscript 2] for Small Independent Samples from Normal Populations with Equal (but unknown) Standard Deviations	p. 233
Estimation of [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Equal (but unknown) Standard Deviations	p. 234
Testing Hypothesis about [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Equal (but Unknown) Standard Deviations	p. 235
Sampling Distribution of X[subscript 1] - X[subscript 2] for Small Independent Samples from Normal Populations with Unequal (and Unknown) Standard Deviations	p. 241
Estimation of [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Unequal (and Unknown) Standard Deviations	p. 242
Testing Hypothesis about [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Unequal (and Unknown) Standard Deviations	p. 244
Sampling Distribution of d for Nonnally Distributed Differences Computed for Dependent Samples	p. 246
Estimation of [mu subscript d] Using Normally Distributed Differences Computed from Dependent Samples	p. 247
Testing Hypothesis about [mu subscript d] Using Normally Distributed Differences Computed from Dependent Samples	p. 249
Sampling Distribution of P[subscript 1] = P[subscript 2] for Large Independent Samples	p. 251
Estimation of P[subscript 1] - P[subscript 2] Using Large Independent Samples	p. 252
Testing Hypothesis about P[subscript 1] - P[subscript 2] Using Large Independent Samples	p. 253
Chi-Square Procedures	p. 272
Chi-square Distribution	p. 272
Chi-square Tables	p. 273
Goodness-of-Fit Test	p. 274
Observed and Expected Frequencies	p. 274
Sampling Distribution of the Goodness-of-Fit Test Statistic	p. 275
Chi-square Independence Test	p. 278
Sampling Distribution of the Test Statistic for the Chi-square Independence Test	p. 279
Sampling Distribution of the Sample Variance	p. 282
Inferences Concerning the Population Variance	p. 284
Analysis of Variance (ANOVA)	p. 299
F Distribution	p. 299
F Table	p. 300
Logic Behind a One-Way ANOVA	p. 302
Sum of Squares, Mean Squares, and Degrees of Freedom for a One-Way ANOVA	p. 304
Sampling Distribution for the One-Way ANOVA Test Statistic	p. 307
Building One-Way ANOVA Tables and Testing the Equality of Means	p. 307
Logic Behind a Two-Way ANOVA	p. 311
Sum of Squares, Mean Squares, and Degrees of Freedom for a Two-Way ANOVA	p. 314
Building Two-Way ANOVA Tables	p. 315
Sampling Distributions for the Two-Way ANOVA	p. 316
Testing Hypothesis Concerning Main Effects and Interaction	p. 316
Regression and Correlation	p. 339
Straight Lines	p. 339
Linear Regression Model	p. 340
Least-Squares Line	p. 342
Error Sum of Squares	p. 345
Standard Deviation of Errors	p. 346
Total Sum of Squares	p. 347
Regression Sum of Squares	p. 347
Coefficient of Determination	p. 348
Mean, Standard Deviation, and Sampling Distribution of the Slope of the Estimated Regression Equation	p. 349
Inferences Concerning the Slope of the Population Regression Line	p. 349
Estimation and Prediction in Linear Regression	p. 350
Linear Correlation Coefficient	p. 350
Inference Concerning the Population Correlation Coefficient	p. 354
Nonparametric Statistics	p. 368
Nonparametric Methods	p. 368
Sign Test	p. 369
Wilcoxon Signed-Ranks Test for Two Dependent Samples	p. 371
Wilcoxon Rank-Sum Test for Two Independent Samples	p. 373
Kruskal-Wallis Test	p. 376
Rank Correlation	p. 379
Runs Test for Randomness	p. 380
Binomial Probabilities	p. 397
Areas under the Standard Normal Curve from 0 to Z	p. 403
Area in the Right Tail under the t Distribution Curve	p. 405
Area in the Right Tail under the Chi-square Distribution Curve	p. 407
Area in the Right Tail under the F Distribution Curve	p. 409
Index	p. 411
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