HPED 2030 Lecture Notes - Lecture 10: Standardized Test, Formula One Group, Analysis Of Variance

• School: Mount Royal University
• Department: Health and Physical Education
• Course: HPED 2030
• Professor: Sommer Christie

Document Summary

Procedures for drawing conclusions about a population based on data collected from a sample. Look at a sample group and extrapolate to a larger population. Parametric statistics considered more powerful because they are: More likely to reject a false null hypothesis . More difficult to achieve significance in nonparametric tests. Observations made from population which are normally distributed. Ordinal population which are not normally distributed t test. Comparing a single mean score to a large known population score. Comparing 2 mean scores that are related (i. e. pre/post data) Comparing 2 mean scores from 2 independent groups of scores (i. e. treatment vs placebo) 1 only 2 mean scores being compared (more than 2 scores = anova) data must be interval or ratio scale data drawn from normally distributed population. Statistics and research methods samples are representative of the population df defined as the number of variables that are free to vary in size n = number of variables df formula.