CMN 3102 Lecture Notes - Lecture 9: Statistical Significance, Analysis Of Variance, Dependent And Independent Variables

• School: University of Ottawa
• Department: Communication
• Course: CMN 3102
• Professor: Philippe Rousseau

Document Summary

Used to test research hypothesis: example: avoiding a fare on public transport in canada differs by marital status. Determines if differences between means of two or more independent groups/sub- samples are significant. Independent groups/sub-samples: if one member/ case in a group does not influence place of another member/ case in that group or another group: example: gender. In practice: ordinal variables can also be used if they are assumed to be interval/ratio: need to specify explicitly/check this assumption, recode values if needed. Assumptions: f-distribution/f-statistics, dependent variable is normally distributed in independent variable levels. Each group/category of the independent variable: at least 30 members/cases. Sample drawn from populations with equal variances on the dependent variable. Statistical significant if less than one of the conventional levels of statistical significance. 01, or 1 in 100, or 1: less than . 05: probability that a tested relationship occurred by chance is less than.