SPSS interpretation (2)

SPSS Interpretation Assignment In this assignment you will be writing up and interpreting SPSS output. This assignment is open book and open notes. You can also use the resources/keys/lectures Dr. Woestehoff posted on Moodle for the Spring 2021 semester. There are videos on Moodle of how to write up and interpret different kinds of tests. It is not open internet or friend/acquaintance/enemy/etc, though, so make sure you don’t talk to anyone about the content of the assignment until you have both submitted your assignment and the deadline has passed. Your work must be your own. You can submit your exam on Moodle by uploading a Word document or a PDF. Please write up each analysis as its own paragraph (instead of one big paragraph) and please report them in the order they are listed here. Each statistical test it on its own page. For each test, you should include all components discussed in lecture and lab for a “full write up”. If the SPSS output looks weird (like the cells have shifted to the right or something) let me know. I have uploaded a Word document and a PDF, so if something looks odd, try opening the other version of the file.

CORRELATIONS /VARIABLES=Age GPA /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE. Correlations Correlations Age GPA Age Pearson Correlation 1 .062 Sig. (2-tailed) .125 N 604 604 GPA Pearson Correlation .062 1 Sig. (2-tailed) .125 N 604 604 Full Write Up: We conducted a Pearson Correlation on the relationship regarding age and GPA, in which there was no correlation in age and GPA , r =1, n = 604, p = 0.125.

ONEWAY Snack_money_spent_monthly BY Academic_major /STATISTICS DESCRIPTIVES /MISSING ANALYSIS /POSTHOC=SCHEFFE ALPHA(0.05). Oneway Descriptives Snack_money_spent_monthly N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound history 190 68.72 29.449 2.136 64.51 72.93 0 100 mathematics 192 56.78 34.298 2.475 51.89 61.66 0 100 education 186 53.14 32.367 2.373 48.46 57.82 0 100 Total 568 59.58 32.733 1.373 56.88 62.28 0 100 ANOVA Snack_money_spent_monthly Sum of Squares df Mean Square F Sig. Between Groups 25102.943 2 12551.471 12.177 .000 Within Groups 582396.761 565 1030.791 Total 607499.703 567 Post Hoc Tests Multiple Comparisons Dependent Variable: Snack_money_spent Scheffe (I) Major 1 = his 2 = mat 3 = edu (J) Major 1 = his 2 = mat 3 = edu Mean Difference (I- J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound history mathematics 11.945 * 3.285 .001 3.88 20.01 education 15.582 * 3.312 .000 7.45 23.71 mathematics history -11.945 * 3.285 .001 -20.01 -3.88 education 3.637 3.303 .546 -4.47 11.74 education history -15.582 * 3.312 .000 -23.71 -7.45 mathematics -3.637 3.303 .546 -11.74 4.47 *. The mean difference is significant at the 0.05 level. Full Write Up: I have conducted a one-way ANOVA to observe whether academic major, (mathematics, history, and education), affects the amount of money spent on snacks monthly. It was observed that academic major did have an

affect on the money that is spent monthly, F (92, 565) = 12.18, p<0.001. Scheffe post hoc tests showed that education (M = 53.14, SD = 32,37), p = 0.546 spent less money on snacks than mathematics (M= 56.78, SD = 34.30) monthly. History (M= 68.72, SD= 29.45), p = 0.001 spent more money on snacks than mathematics looked monthly. History spent more money on snacks than education monthly, p<0.001.

Full Write Up: I had conducted a repeated measure t test to observe the effect of the color of pen used and the exam scores. There was no significant of black pen (M= 77.55, SD = 15.67) or blue pen (M= 78.73, SD = 17.25) on the exam scores, t(10) = 0.164, p = 0.873, 95%Cl [-14.91, 17.27]