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Final

CRIM 320 Final - Interpreting Outputs (SPSS Demystified).pdf

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School
Department
Criminology
Course
CRIM 320
Professor
Martin Andresen
Semester
Spring

Description
One-sample t test  Objective = Determine whether mean of ONE sample differs significantly from the known/estimated population mean o RQ: Is Vancouver’s poverty rate significantly different from national poverty rate o Null – Vancouver rate equal to national average (H0: u= 19) o Alt – Vancouver rate not equal to national average (1 : u ≠ 19) One-Sample Statistics Std. N Mean Deviation % 125 16 5.3437 poverty One-Sample Test Test Value = 19 t df Sig. (2-tailed) Mean Difference 1.556 124 .001 3  Results 1. Test of significance  Mean difference = 3  T-value = 1.556  P-value = 0.001  If (p value > .05) = Null not rejected = sample not sig different than population – due to sampling error  If (p value ≤ .05) = Null rejected = sample significantly different than population – greater or less than? o Report mean – greater/lesser? (Van = 16, National = 19 – van sig less poverty)  Effect size = mean difference / std deviation o S (0.2) M (0.5) L (0.8) o The amount of difference between SM and PM in terms of standard deviation units  Eg - 3/5 = 0.6 = medium  Assumptions o Observations are independent = participants do not influence each other o Dependent variable is normally distributed (else problematic, statistical procedure untrustworthy, p-values inaccurate, standard deviations not useful in measuring variability) Independent samples t test  Objective = Whether Two independent groups differs significantly on dependent variable of interest o RQ: Is there difference in average pain levels, between MIS and Traditional surgical procedure? o Null – Pain level scores for Trad and MIS is equal in the population (H : u0 = uM) o Alt – Pain level scores for Trad and MIS is NOT equal in the population (H : uT ≠ uM) 0 Group Statistics procedure N Mean Std. Deviation pain MIS 15 5.7333 1.66762 Traditional 15 7.8667 1.59762 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means Sig. (2- Mean Std. Error F Sig. t df tailed) Difference Difference pain Equal variances .005 .943 -3.578 28 .001 -2.13333 .59628 assumed Equal variances not -3.578 27.949 .001 -2.13333 .59628 assumed  Results 1. Levene’s Test = test for whether population variances are equal or not  F-value (0.005)  P-value (0.948)  greater, null not rejected, variances are equal, first row  p value > .05 = null NOT rejected, population variances equal = FIRST ROW  p value ≤ .05 = null rejected, population variances NOT equal = SECOND ROW 2. Test for equality of means  T-value = 3.578  P-value = 0.001  If (p value > .05) = Null not rejected = pain levels same b/t two groups – sampling error  If (p value ≤ .05) = Null rejected = pain levels differ b/t two groups o Report mean – which lower/higher (MIS = 5.7, Trad = 7.8 -- MIS had less pain)  Effect size = t √(N1+n2/(n1n2)) o S (0.2) M (0.5) L (0.8) o The amount of difference in scores between 1 and 2 in terms of standard deviation units  Eg - -3.578√(15+15/(15*15)) = -1.31 = very large  MIS 1.31 SD lower pain than Trad  Assumptions o Observations are independent = participants do not influence each other o Dependent variable is normally distributed (pain levels scores) o Variances are equal in population (can compromise if sample sizes are unequal – levene test help address this assumption) Dependent samples t test  Objective = whether means of two related groups differ significantly on dependent variable of interest o RQ: – Does going to prison have an impact on offending rate after and before? o Null – Difference on offending rate, before and after going to prison, equal to 00(H : uB - uA = 0) o Alt – Difference on offending rate, before and after going to prison, NOT equal to 0 0H : uB - uA ≠ 0) Paired Samples Statistics Mean N Pair 1 beforep 56.6963 30 afterp 55.2927 30 Paired Samples Test Paired Differences Std. Std. Error Sig. (2- Mean Deviation Mean t df tailed) Pair beforep - 1.4036 59.17465 10.80376 .130 29 .898 1 afterp 7  Results 1. Test of significance  T-value = 0.13  P-value = 0.898  If (p value > .05) = Null not rejected = offending rate same before/after going to prison – sampling error  If (p value ≤ .05) = Null rejected = offending rate differ, before and after going to prison o Report mean – greater/lesser? (Before 56, After 55 – after prison offend less) o In this sample, p greater, so not different, null not rejected  Effect size = mean difference / std deviation of difference scores o S (0.2) M (0.5) L (0.8) o The amount of difference in offending rates between before and after going to prison in terms of standard deviation units  Eg – 1.4/59.17 = 0.02 – very very small  Assumptions o Observations are independent within groups= offender do not influence each other o Scores normally distributed in population One-way ANVOA  Objective = two or MORE groups differ significantly on a on dependent variable of interest o RQ: does number of words recalled depend on the type of learning strategy used? o Null – Average Memory scores for A B C is equal in the populatio0 (H : uA = uB = uC) o Alt – At least one of the learning strategy has a score that is significantly different from the others Descriptives wordrecall N Mean Std. Deviation Test of Homogeneity of Variances strategy A 10 8.9000 1.52388 wordrecall strategy B 10 10.2000 1.39841 Levene Statistic df1 df2 Sig. strategy C 10 4.7000 1.49443 .021 2 27 .980 Total 30 7.9333 2.77841 Multiple Comparisons ANOVA
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