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Inferential Statistics

Learn how to use SPSS to run T-tests, ANOVA, and correlation analysis, with step-by-step instructions and interpretation of results.

jamessrobinson
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Inferential Statistics

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  1. Inferential Statistics Overview

  2. SPSS Steps Open SPSS data file Click on ANALYZE Click on COMPARE MEANS Click on INDEPENDENT SAMPLES T TEST Select continuous dependent variable Select nominal grouping variable Define groups (1 and 2) Click OK Interpreting Output Check means and group sizes Look EQUAL VARIANCES ASSUMED Note t value, df, and significance (two tailed) If significance ≤ .05, report t = value, df = value, p = significance T-test

  3. Differences Study What accounts for different oral proficiency ratings? • ratings on informational interview are dependent variable • student characteristics possible independent variables Theory--applied learning experiences enhance student performance in the classroom Hypothesis—completing an internship will increase ratings on the informational interview

  4. T-test Output

  5. T-test Narrative Hypothesis—Completing an internship will increase oral and written competency ratings. Result—Completing an internship had no effect on one dimension (invention) of oral competency ratings (t = -.028, df = 56, p = .98). Found no support for hypothesis.

  6. SPSS Steps Open SPSS data file Click on ANALYZE Click on COMPARE MEANS Click on ONE WAY ANOVA Select continuous dependent variable Select nominal/ordinal factors Click POST HOC TESTS Select TUKEY and significance level Click CONTINUE Click OK Interpreting Output Note F ratio, df (between and within), and significance If significance ≤ .05, report F(dfbetween,dfwithin) = value, p = significance Tukey output indicates which groups are different from each other ANOVA

  7. Differences Study What accounts for different written proficiency ratings? • ratings on portfolio are dependent variable • different instructor possible independent variables Theory--instructor ratings should be uniform. Question—Will identity of instructor influence ratings on the portfolio?

  8. ANOVA Output

  9. Tukey Output

  10. ANOVA Narrative Hypothesis—Instructor teaching COM400 will not influence oral and written competency ratings. Result—Instructor teaching COM400 influenced one dimension (invention) of written competency ratings (F (4,100) = 11.98, p = .0001). Instructors 3 and 5 graded harder than Instructors 1, 2 and 4. Found no support for hypothesis.

  11. SPSS Steps Open SPSS data file Click on ANALYZE Click on CORRELATIONS Click on BIVARIATE Select continuous dependent variable Select continuous independent variable Select PEARSON corr coeff, two tailed test and flag significance correlations Click OK Interpreting Output Look above or below the diagonal Note correlation coefficient and significance (two tailed test) If significance ≤ .05, report r = value, p = significance and strength of relationship r = ≤ .39, weak relationship r = .40-.69, moderate relationship r = .70-.99, strong relationship Correlations

  12. Relationship Study What are you willing to do for a friend? • willingness to offer emotional support to a CSF is the independent variable • willingness to offer instrumental support to a CSF is a dependent variable THEORY—Social exchange theory Hypothesis—A relationship exists between emotional support offered a CSF and instrumental support offered a CSF.

  13. Correlation Output

  14. Correlation Narrative Hypothesis—A relationship exists between emotional support offered a CSF and instrumental support offered a CSF. Result—A relationship exists between emotional support offered a CSF and instrumental support offered a CSF • platonic friend (r = .65, p = .005) moderate • friends with benefits (r = .66, p = .004) moderate Support was found for hypothesis.

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