KNES 375 Chapter 5: 375 Unit 5 Part 1
KNES 375 – Unit 5 Notes (Part 1)
Inferential Statistics
Overview
• Sampling Theory
• Null Hypothesis
• Sampling Error
• Students’ t-Test
o 2 Independent Groups
o 2 Dependent Groups
• One-Way ANOVA
• One-Way ANOVA with Repeated Measures
• Two-Way ANOVA with Repeated Measures
• Two-Way ANOVA, Factorial Design
• WILL NOT GET EQUATION FOR MEAN AND STANDARD DEVIATION ON THE MIDTERM
Introduction
• Is there a difference between the group means?
• E.g., You have a high school Physical Education class and you want to divide them into two
volleyball teams of similar height
o Random Selection
o Mean height will be different
▪ Is this because of a sampling error?
▪ OR is there a significant height difference?
• Essentially, you want to compare two groups!
o Is group 1 similar to group 2?
o E.g., do alpine skiers have a different VO2max than speed skaters?
▪ Alpine skiers = 53 mL/kg/minute
▪ Speed skaters = 61 mL/kg/min
• At first glance, they appear to be different, but is this difference
significant? Use a t-test to figure out the magnitude of difference
o P value must be less than selected α value
o Dependent t-test for teams over a time frame, tested over and over again
o Should use an independent t-test for this
• If differences are statistically significant then the difference between the groups is NOT due to
sampling error.
• If differences are not statistically significant then the difference between groups is simply due to
sampling error.
o A small expected difference
In the big scheme of things…
• DATA SET = Want to use our data sets for parametric statistics – want interval/ratio data. Want
similarity of units (measuring the same thing)