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Interpreting and using statistics in psychological research / Andrew N. Christopher.

By: Christopher, Andrew N.
Material type: materialTypeLabelBookCall no.: BF39 .C476 2017Publication: Los Angeles : SAGE Publications, c2017Description: xxv, 552 p. : ill.ISBN: 9781506304168; 1506304168.Subject(s): Psychology -- Statistical methods | Psychometrics | Psychology -- Research -- Methodology
Contents:
Why do I have to learn statistics? The value of statistical thinking in life -- Basics of quantitative research: Variables, scales of measurement, and an introduction to the statistical package for the social sciences (SPSS) -- Describing data with frequency distributions and visual displays -- Making sense of data: Measures of central tendency and variability -- Determining "high" and "low" scores: The normal curve, z scores and probability -- Drawing conclusions from data: Descriptive statistics, inferential statistics, and hypothesis testing -- Comparing two group means: The independent samples t test -- Comparing two repeated group means: The paired samples t test -- Comparing three or more group means: The one-way, between-subjects analysis of variance (ANOVA) -- Comparing three or more repeated group means: The one-way, repeated-measures analysis of variance (ANOVA) -- Analyzing two or more influences on behavior: Factorial designs for two between-subjects factors -- Determining patterns in data: Correlations -- Predicting the future: Univariate and multiple regression -- When we have exceptions to the rules: Nonparametric tests -- Bringing it all together: Using your statistical toolkit.
List(s) this item appears in: TUMED-New Book 2018-October (Foreign)
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Includes bibliographical references and index.

Why do I have to learn statistics? The value of statistical thinking in life -- Basics of quantitative research: Variables, scales of measurement, and an introduction to the statistical package for the social sciences (SPSS) -- Describing data with frequency distributions and visual displays -- Making sense of data: Measures of central tendency and variability -- Determining "high" and "low" scores: The normal curve, z scores and probability -- Drawing conclusions from data: Descriptive statistics, inferential statistics, and hypothesis testing -- Comparing two group means: The independent samples t test -- Comparing two repeated group means: The paired samples t test -- Comparing three or more group means: The one-way, between-subjects analysis of variance (ANOVA) -- Comparing three or more repeated group means: The one-way, repeated-measures analysis of variance (ANOVA) -- Analyzing two or more influences on behavior: Factorial designs for two between-subjects factors -- Determining patterns in data: Correlations -- Predicting the future: Univariate and multiple regression -- When we have exceptions to the rules: Nonparametric tests -- Bringing it all together: Using your statistical toolkit.

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