Use the following information to interpret the main effect for the correlation matrix below. Correlations Correlations feelingsofguilt Feel lonely COMPUTE COMPUTE feelingsofguilt-v82| +v83+v84+v85 + v86+v87+v88 + v89 + v90 + v91 + selfworth COMPUTE selfworth-v98+ victimization Feel lonely-v66+v92+v93+v94+ v99v100+ v101 COMPUTE victimization=v181 + v183+ v185 + v67+v68 v95 + v96 + v97 + v102 + v103 v187 Feel lonely COMPUTE Pearson Correlation Feel lonely-v66+v67 + v68 Sig. (2-tailed) N .022 -.293 .084 215 .000 .000 3416 3203 3310 3324 Pearson Correlation 022 .176 -.245 + Sig. (2-tailed) .000 .000 feelingsofguilt COMPUTE feelingsofguilt-v82 + v83 + v84 v85+v86+v87 + v88 + v89 + + v90 191 192 + v93 + v94 + v95 + v96 + v97 215 N 3203 3225 3150 3150 selfworth COMPUTE Pearson Correlation -293 .176 1 -.057 selfworth=v98 + v99+ v100 + Sig. (2-tailed) .000 .000 .001 v101 v102v103 N 3310 3150 3341 3267 victimization COMPUTE Pearson Correlation 084 -.245 -.057 1 victimization=v181+ v183 + Sig. (2-tailed) .000 .000 .001 v185 v187 N 3324 3150 3267 3369 Feel Lonely: The Lower numbers on the distribution is equal to feeling lonely. Higher numbers indicate the respondent does not feel lonely. Levels of Guilt: Lower numbers on the distribution indicate higher levels of guilt. Self worth: Higher numbers on the distribution indicate high self worth. Victimization: Higher numbers on the ditribution indicate lower levels of victimization. Lower numbers on the distribution indicate high levels of victimization. Quick Reference Guide for Interpretations The following would be what you will need to report when interpreting the variables at the following levels of measurement: Nominal Level Ordinal Level Variables Variables Interval Level Measures Ratio Level Measures Frequencies Frequencies Mean Mean Percentages Percentages Mode Median What is compelling What is compelling Standard Deviation Minimum Score Maximum Score Standard Deviation Minimum Score about the data? about the data? Frequencies* Percentages* What is compelling about the data? Maximum Score Frequencies* Percentages* What is compelling about the data?