General information you should know: 1. experimental design: a group of subjects who receive various levels of the independent variable 2. dependent variable: variable that is measured to find effect of independent variable 3. factor or independent variable: manipulated in experiment 4. levels: different forms or strengths 5. replication: repeated subjects within a control or experiment group 6. controls: ppl that don’t receive manipulated independent variable 7. paired vs. independent replicates: paired is exposed to all, independent not 8. randomization: use of some random method to assign subjecs to a group 9. Why are statistics necessary for analyzing scientific data? Variation to judge whether differences we observe btwn populations are real or due to chance 10. What does sum of squares tell you about a data set? Measure of variation within a group 11. What is meant by “probability” in the context of a statistical test? Due to chance alone 12. Why is replication / sufficient sample size necessary in an experiment? To account for natural variation in population 13. Basic structure of statistical test: null hypothesis: assumption that two groups are the same 14. test statistic ( t (Ttest), F: ANOVA, etc.): measure of magnitude of variation btwn groups 15. probability (p-value): low= not likely due to chance, 16. statistical significance: probability less than 0.05, reject null 17. Why are measures like standard error used when graphing mean values of a data set? Measure of variation within a group 18. Why use an ANOVA rather than multiple t-tests when