Tough Test Questions? Missed Lectures? Not Enough Time?
Fortunately, there's Schaum's. This all-in-one-package includes more than 750 fully solved problems, examples, and practice exercises to sharpen your problem-solving skills. Plus, you will have access to 20 detailed videos featuring Math instructors who explain how to solve the most commonly tested problems--it's just like having your own virtual tutor! You'll find everything you need to build confidence, skills, and knowledge for the highest score possible.
More than 40 million students have trusted Schaum's to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills.
This Schaum's Outline gives you
• 897 fully solved problems
• Concise explanations of all course fundamentals
• Information on conditional probability and independence, random variables, binominal and normal distributions, sampling distributions, and analysis of variance
Fully compatible with your classroom text, Schaum's highlights all the important facts you need to know. Use Schaum’s to shorten your study time--and get your best test scores!
Schaum's Outlines--Problem Solved.
Author(s): John J. Schiller, R. Alu Srinivasan, Murray R. Spiegel
Series: Schaum’s Outline
Edition: 4
Publisher: McGraw-Hill Education
Year: 2012
Language: English
Commentary: True PDF
Pages: 432
City: New York, NY
Tags: Regression; Bayesian Inference; Statistics; Probability Theory; Hypothesis Testing; Nonparametric Models
Contents......Page 6
Part I: Probability......Page 10
Sample Spaces......Page 12
Events......Page 13
Some Important Theorems on Probability......Page 14
Assignment of Probabilities......Page 15
Independent Events......Page 16
Fundamental Principle of Counting: Tree Diagrams......Page 17
Combinations......Page 18
Stirling’s Approximation to n!......Page 19
Discrete Probability Distributions......Page 43
Distribution Functions for Discrete Random Variables......Page 44
Continuous Random Variables......Page 45
Graphical Interpretations......Page 47
Joint Distributions......Page 48
Change of Variables......Page 50
Probability Distributions of Functions of Random Variables......Page 51
Conditional Distributions......Page 52
Applications to Geometric Probability......Page 53
Definition of Mathematical Expectation......Page 84
Some Theorems on Expectation......Page 85
The Variance and Standard Deviation......Page 86
Moments......Page 87
Some Theorems on Moment Generating Functions......Page 88
Characteristic Functions......Page 89
Variance for Joint Distributions. Covariance......Page 90
Conditional Expectation, Variance, and Moments......Page 91
Other Measures of Central Tendency......Page 92
Skewness and Kurtosis......Page 93
Some Properties of the Binomial Distribution......Page 117
The Normal Distribution......Page 118
Some Properties of the Normal Distribution......Page 119
Relation Between the Binomial and Poisson Distributions......Page 120
The Hypergeometric Distribution......Page 121
The Uniform Distribution......Page 122
The Beta Distribution......Page 123
Student’s t Distribution......Page 124
The F Distribution......Page 125
Miscellaneous Distributions......Page 126
Part II: Statistics......Page 160
Sampling With and Without Replacement......Page 162
Sample Statistics......Page 163
Sampling Distribution of Means......Page 164
Sampling Distribution of Proportions......Page 165
The Sample Variance......Page 166
Sampling Distribution of Variances......Page 167
Other Statistics......Page 168
Frequency Distributions......Page 169
Computation of Mean, Variance, and Moments for Grouped Data......Page 170
Confidence Interval Estimates of Population Parameters......Page 204
Confidence Intervals for Means......Page 205
Confidence Intervals for the Variance of a Normal Distribution......Page 206
Maximum Likelihood Estimates......Page 207
Type I and Type II Errors......Page 222
One-Tailed and Two-Tailed Tests......Page 223
P Value......Page 224
Special Tests of Significance for Large Samples......Page 225
Special Tests of Significance for Small Samples......Page 226
The Chi-Square Test for Goodness of Fit......Page 228
Yates’ Correction for Continuity......Page 230
Coefficient of Contingency......Page 231
Regression......Page 274
The Method of Least Squares......Page 275
The Least-Squares Line......Page 276
The Least-Squares Parabola......Page 277
Standard Error of Estimate......Page 278
The Linear Correlation Coefficient......Page 279
Rank Correlation......Page 280
Probability Interpretation of Regression......Page 281
Sampling Theory of Regression......Page 282
Correlation and Dependence......Page 283
One-Way Classification or One-Factor Experiments......Page 323
Linear Mathematical Model for Analysis of Variance......Page 324
Expected Values of the Variations......Page 325
Analysis of Variance Tables......Page 326
Notation for Two-Factor Experiments......Page 327
Variations for Two-Factor Experiments......Page 328
Analysis of Variance for Two-Factor Experiments......Page 329
Two-Factor Experiments with Replication......Page 330
Experimental Design......Page 332
The Sign Test......Page 357
The Mann–Whitney U Test......Page 358
The Runs Test for Randomness......Page 359
Further Applications of the Runs Test......Page 360
Spearman’s Rank Correlation......Page 361
Prior and Posterior Distributions......Page 381
Sampling From a Binomial Population......Page 384
Sampling From a Poisson Population......Page 385
Sampling From a Normal Population with Known Variance......Page 386
Improper Prior Distributions......Page 387
Conjugate Prior Distributions......Page 388
Bayesian Point Estimation......Page 389
Bayesian Interval Estimation......Page 391
Bayesian Hypothesis Tests......Page 392
Bayes Factors......Page 393
Bayesian Predictive Distributions......Page 395
The Gamma Function......Page 420
Special Integrals......Page 421
Appendix B: Ordinates y of the Standard Normal Curve at z......Page 422
Appendix C: Areas under the Standard Normal Curve from 0 to z......Page 423
Appendix D: Percentile Values for t[sub(p)] Student’s t Distribution with v Degrees of Freedom......Page 424
Appendix E: Percentile Values x[sup(2)][sub(p)] for the Chi-Square Distribution with v Degrees of Freedom......Page 425
Appendix F: 95th and 99th Percentile Values for the F Distribution with v1, v2 Degrees of Freedom......Page 426
Appendix H: Random Numbers......Page 428
E......Page 429
P......Page 430
Z......Page 431
L......Page 432
W......Page 433
