STA221 Exam Review Sheet

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Olga Fraser

For CRD, indep random samples need to be selected for each treatment OR treatments have to be randomly assigned to experimental unitstiog H =Type II error; Multiple comparisons: controls for TypeI error called "experimentwise error rate" ot CI interpretation for (µ -µ1):21) -ve/+ve =cant conclude that either mean is sig. larger, comparisonwise both µ are not sig. diff [if centre of interval <0 then bigger µ value is larger, if >0 then smaller µ value is larger; 2) both -ve= µ is 2ig larger than µ 3) bo1h +ve= µ is sig. l1rger than µ 2 Factors: variables whose effect on the response is of interest to the experimenter; Qualitative factors: numerical; Factor levels: values of factor utilized in the experiment Not satisfied=nonparametric (Kruskal-Wallis H-Test (levels of qualitative factors=non-numerical e.g. levels of qualitative factor Location are N/E/W/S)(levels of quantitative factors are numerical e.g. #of…, the GPAs); Levels of Factor: specific values of the factor; Treatments: factor-level combinations(if one factor, then levels=treatments) Designed: control over levels of factor Obs: no control Completely Randomized Design: design where an independent random sample is selected for each level of the factor Model in CRD: y = µij ϵ (iesidijl: ) SST (sumofsquaresfortreatments): calculates variation between treatment means SST= SSE (sumofsquaresforerror): measures sampling variability within the treatment due to sampling errors SSE=(n -1)1 12 + (n2-1)s2+…(n -1ks k2 [sk2sample variances for the k treatments) MST(meansquarefortreatments): measures variability among the treatment means MST=SST/k-1 MSE(meansquareforerror): measures sampling variability within the treatments MSE=SSE/n-k ~ [SSE=SS (total)T] F=MST/MSE ANOVA=robustmethod when assumption of normality isnt satisfied, Boxplots=check for equal variances Number of pairwise comparisons of treatment means: c= k(k-1)/2 Randomized Block Design: Assumptions: Blocks are rando
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