Inferential Statistics (Introduction to Statistics) - Softcover

Inhaltsangabe

This friendly but authoritative text explains the use and interpretation of basic statistical significance tests. Contents: Chapter 1 - Making inferences about populations: Generalizing from a sample to a population; Probability and chance; Statistical tests; Type-1 and Type-2 errors; Choosing an acceptable significance level; The Null Hypothesis; Interpreting a non-significant result; Directional and non-directional tests. Chapter 2 - The characteristics of significance tests: Using statistical tables; Parametric and non-parametric tests of significance; Selecting a suitable statistical test; The sum of squares (SS); Degrees of freedom (df); The standard error (SE); How statistical tests in this unit are organized. Chapter 3 - Measurements that occur in pairs: One-sample t-test (related t-test); Degrees of freedom in a one-sample t-test; Drawing conclusions from significant results; What if the result is not significant? Wilcoxon test (T); Sign test; What if tests disagree? Which test should we use? Chapter 4 - Measurements that are not in pairs: Two-sample t-test; Interpreting significant and non-significant outcomes; Mann-Whitney (U) test; What if our groups are too large for tables D and E? An example using the z calculation. Chapter 5 - Categories in a single sample using chi-squared: Degrees of freedom in chi-squared; What does the Chi-sq result mean? Yates's correction for continuity; Explaining a significant outcome; The Null Hypothesis need not be that all probabilities are equal; Sign test (again). Chapter 6 - Categories in two or more samples: Comparing Victoria's sample with Albert's; Median test; Comparing the outcomes of various tests; Rules for using chi-squared; More than two categories; more than two samples; Determining the number of df. Answers to the self-assessment questions. Glossary. Statistical tables. Summary of the statistical methods in this unit.

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