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Statistics in SPSS Lecture 9

Statistics in SPSS Lecture 9. Petr Soukup, Charles University in Prague. ALTERNATIVES TO T-TESTS (NON-PARAMETRIC TESTS). Alternatives to T-tests. Alternatives in SPSS. Analyze-Nonparametric tests-One sample Analyze-Nonparametric tests-Independent samples Analyze-Nonparametric tests-Paired

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Statistics in SPSS Lecture 9

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  1. Statistics in SPSSLecture 9 Petr Soukup, Charles University in Prague

  2. ALTERNATIVES TO T-TESTS(NON-PARAMETRIC TESTS)

  3. Alternatives to T-tests

  4. Alternatives in SPSS Analyze-Nonparametric tests-One sample Analyze-Nonparametric tests-Independent samples Analyze-Nonparametric tests-Paired Example: alternative to ANOVA: Analyze-Nonparametric tests-Independent samples-Compare Medians (Kruskal-Wallis with multiple comparisons)

  5. CONTINGENCY TABLES

  6. Contingency table (CT) Combine at least two (nominal or ordinal) variables in one table Main goal: to analyze relationship between variables Descriptive stats in CT: observed counts and percentages (row, column and total) Analyze-Descriptive statistics-Crosstabs (Cells)

  7. Test for CT Test of independence: Chi-square H0: variables are independent (in the whole population) H1: variables are dependent (in the whole population) Analyze-Descriptive statistics-Crosstabs (Statistics) Computation: comparison of observed and expected (by H0) counts Note: for correct computation 80 % of exp. Counts>5 and no zeros

  8. Contingency coefficient (CC) Effect size for CT Measurement of relationship between variables Usually computed from chi-square Values between 0 (no relationship) and 1 (perfect relationship) Mostly used coefficient: Cramer’s V Analyze-Descriptive statistics-Crosstabs (Statistics)

  9. Detailed analysis in CC For proven relationship (reject H0) Sign scheme for adusted standardized residuals Once again rule of values -2 and +2 Signs instead of residuals and it’s meaning Analyze-Descriptive statistics-Crosstabs (Statistics) and MS Excel tool for sign scheme

  10. HW

  11. HW9 Try to analyze relationship between two nominal or ordinal variables by contingency tables. Interpret results.

  12. Thanks for your attention

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