Student one way between ANOVA instructions Jasp version

Workshop One-way Between Subjects ANOVA Test for Homogeneity Post Hoc Test  ANOVA – analysis of variance  Used to if there is determine significant difference in the DV (means) between levels of the IV  One-way (one IV variable)  Between subjects (difference subject in each level)  ANOVA tell us if there is a difference – require a post hoc to determine which groups are significantly different.  Assumption – Homogeneity – check the variances to determine if they are similar across the levels  Assumption of Normality – check across levels to determine if they are normally distributed  As with a t-test we can only infer causation if we are using a true experiment otherwise association are inferred (quasi- experiment)  When to use a non-parametric test – assumptions violated, unequal n  Non Parametric -Between Subject - Krusall Wallis H Test- post hoc MWU

Workshop One-way Between Subjects ANOVA Test for Homogeneity Post Hoc Test Example 3 – use PETREND Example Question: Participants were divided into the following 5 groups (ADJUSTGP) according to their ADJUST score: LOW1 (scores from the 35 to 59), LOW2 (60 to 69), MEDIAN (70 to 79), HIGH1 (80 to 89), and HIGH2 (scores greater than 90). Are SCST scores different for the ADJUSTGPs? If so, which groups are more resourceful? DV = _________________________ IV =______________________________________________________________________ _____________________________________________________________________________________ _____________________________________________________________________________________ _________________________________________________________________________________ Sub-setting and Grouping is done for this question 1. Anaylsis -----Descriptives-----ADJUST and SCST -----include Min and Max ---use min, max for subset if required

Descriptive Statistics -Place SCST, and ADJUST , into the Variable Box -Means, SD, min, max for SCST and ADJUST -Place ADJUSTGP into variable box -Tables- Frequency tables – ADJUSTGP WARDDescriptive Statistics jaspDescriptives::Descriptives(         version = "0.17.2",         formula = ~ SCST + ADJUST + ADJUSTGP,         frequencyTables = TRUE) Descriptive Statistics   SCST ADJUST ADJUSTGP Valid 161 161 161 Missing 0 0 0 Mean 17.530 76.129 Std. Deviation 25.522 13.775 Minimum -69.000 35.000 Maximum 76.000 104.000 Note.  Not all values are available for Nominal Text variables Frequency Tables Frequencies for ADJUSTGP ADJUSTGP Frequency Percent Valid Percent Cumulative Percent high1 41 25.466 25.466 25.466 high2 29 18.012 18.012 43.478 low1 20 12.422 12.422 55.901 low2 29 18.012 18.012 73.913 median 42 26.087 26.087 100.000 Missing 0 0.000     Total 161 100.000     Note.  The following variables have more than 10 distinct values and are omitted: SCST, ADJUST.

ADJUST has been split into 5 groups , LOW1 (scores from the 35 to 59), LOW2 (60 to 69), MEDIAN (70 to 70), HIGH1 (80 to 89), and HIGH2 (scores greater than 90). Testing Assumptions: Normality  Go to Descriptives in tool bar  Place SCST in variable box and ADJUSTGP in Split box  Click on Distribution Descriptive Statistics jaspDescriptives::Descriptives(         version = "0.17.2",         formula = ~ SCST,         shapiroWilkTest = TRUE,         splitBy = "ADJUSTGP") Descriptive Statistics SCST   high1 high2 low1 low2 median Valid 41 29 20 29 42 Missing 0 0 0 0 0 Mean 19.589 33.315 -0.743 7.425 20.300 Std. Deviation 21.173 20.931 26.307 26.985 23.748 Shapiro-Wilk 0.976 0.971 0.933 0.984 0.979 P-value of Shapiro-Wilk 0.516 0.589 0.174 0.934 0.640 Minimum - 38.000 -4.000 -69.000 -54.000 -34.000 Maximum 55.000 76.000 45.000 65.000 69.000  Check the p values for Shapiro-Wilk test and the p values