1. Lab 2 instruction

2.  a collection of statistical methods to compare several groups according to their means on a quantitative response variable  One-Way ANOVA a special case of ANOVA when a single factor is used

3.  Response: LSA value (lipid- bound sialic acid)  4 groups: 1(Control), 2(benign), 3(Primary), 4(Recurrent)  350 patients in each group

4.  Independence: both within and across the groups  Normality: population distributions of all groups are normal  the populations have equal standard deviations

5.  Independence: setup of the experiment  Normality: boxplot / Q-Q plot  Equal std devs: ◦ Boxplot ◦ Descriptive summary “Rule of thumb”: the ratio of the largest sd and the smallest sd < 2 ◦ Levene’s test

6.  In Levene’s test Levene’s test of equal variances p-value>0.05

7.  Analyze -> Descriptive stats -> explore Descriptive summary; boxplot; Q-Q plot; Levene’s test.

8. One-way ANOVA

9. Analyze -> Compare Means -> One-Way ANOVA

10.  Full model: different group mean Reduced model: grand mean  Calculate F by hand:

12.  Multiple comparisons: test the difference between each pair of means Tukey test Scheffe test Multiple Comparison

13.  In Post Hoc..

15. Multiple Comparison  number of pairwise comparisons  Look at p-value of the hypothesis test of equality of two means  Check whether the confidence interval contains zero or not

16.  compare cancer patients (group 2, 3 and 4 ) with healthy individuals (group 1).

17.  In Contrasts..

18. Another tool in SPSS: ScatterPlot If two variables are somehow related, there would be some trend in the scatter plot.

19.  Scatter plot of “LSA” V.S. “ID”-- LSA in Y axis ID in X axis  Different groups can be denoted using different markers Scatter plot