Understanding Significance Testing, Volume 73SAGE, 1990 - 76 pages "The book begins with a clear and readable explanation of the idea of the sampling distribution....This text should be useful to the nonstatistical social researcher who wants to understand the concept of significance testing." --Social Research Association News "Good for refreshing a few basic ideas." --Journal of the American Statistical Association Significance testing is the most used, and arguably the most useful, of all techniques for analyzing social science data. In this practical volume, Mohr first defines basic terms such as variance, standard deviation, and parameter. He then carefully outlines the uses of significance testing and examines sampling distributions, probability distributions, and normal and t-tests of significance. Readers at all levels of research experience, from the first-semester student to the seasoned practitioner, will profit from this handy volume. |
Table des matières
Acknowledgments | 4 |
The Sampling Distribution | 13 |
Interval Estimation | 28 |
Significance Testing | 49 |
The Functions of the Test | 67 |
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Expressions et termes fréquents
2.33 standard deviations ambition and tolerance assume average absolute deviation basis causal inference Central Limit Theorem classical inference confidence intervals correlation critical value degrees of freedom difference-of distance in terms distance of ux draw a sample established critical distance example Express the critical fact factors formula function horizontal axis individual infinite interval estimate known sampling distribution large number large samples Let us say magnitude mathematical mean tolerance score negative normal curve normal distribution null hypothesis number of standard observed sample one-tailed test population mean population parameter possible probability is 95 random sampling Regression reject the null relationship is zero relevant result sample difference-of-means sample mean tolerance sample relationship sample statistic sample value sampling distri seven steps significance testing simply sort statement straw-man claim subgroups tails tion true Type II error unambitious unit of analysis variable worst-case X I will calculate Y₁ Z scores µy₁