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COMM 250 Agenda - Week 12. Housekeeping TP3a – Due Wednesday, 6/11 RP2 – Due Thursday, 6/12 RAT6 – Monday, 6/16 (No specific P-RAT that parallels RAT6) Lecture RAT 5 Inferential Statistics, Continued. Types of Variables. Definition: “Concepts that take on 2 or more values”
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COMM 250 Agenda - Week 12 Housekeeping TP3a – Due Wednesday, 6/11 RP2 – Due Thursday, 6/12 RAT6 – Monday, 6/16 (No specific P-RAT that parallels RAT6) Lecture RAT 5 Inferential Statistics, Continued
Types of Variables Definition: “Concepts that take on 2 or more values” • Nominal = Equal Groupings • (Gender, Race, Political Party) • Ordered = Some Priority or Rank • Ordinal • Rank Order: (Hottest Days, Top Ten) • Interval • Equal Intervals: (Temp., IQ, Scale from 1-7) • Ratio • Interval, with a “True” Zero (Weight; Height)
t-Test and ANOVA The t-test • 2 independent samples (groups) • Are the samples different ? • A Different Online Example Analysis of Variance (ANOVA) • 2 or more levels of a (Discrete) IV • Often Multiple IVs; Single DV • Factorial Designs • Main Effects; Interactions
Multiple Regression • IV(s) - Continuous • ANOVA is specific case of Regression • One DV • Least-Squares Method • Looking for best fit of data to a Regression line: • Insurance, College Admissions • “Goodness of Fit” Estimation • ITE 10
In-Class Team Exercise # 10 What are the 3 most important variables used to determine : • A person’s Car Insurance rates? • A person’s Life Insurance rates? • A person’s Admittance to College? -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Submit a Team version (only) ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Multiple Regression • IV(s) - Continuous • ANOVA is specific case of Regression • One DV • Least-Squares Method • Looking for best fit of data to a Regression line: • SATs, GREs • “Goodness of Fit” Estimation • Back to the Issues of Free Will & Determinism
Analyzing Relationships Between Variables Correlation • Two Variables Can Have: • A Linear or non-linear relation - (or be Totally Unrelated) • A Positive or Negative relation
Measures of Correlation • Bivariate Correlation coefficient (r) • A measure of the strength & direction of the relationship between 2 variables • Coefficient of determination (“r-squared”) • Explains the extent to which changes in one variable account for changes in the other • Describes the % of variance in Var. X accounted for by Var. Z
Measures of Correlation • Correlation matrix • A convenient way to display many bi-variate correlations • Multiple correlation • measures the effect of two or more variables together on a third variable • Partial correlation • Measures the relationship between two variables while controlling for a third variable
Errors In Inference • Type I Error • Rejecting The Null Inappropriately Situations Where ‘Type I’ Errors are Costly • Banning Saccharine (1970s) • Breast Cancer Risk & Advice about Mammograms • Type II Error • Failing To Reject The Null When It Is False Situations Where We Can’t Afford a ‘Type II’ Error • Radar (Air Traffic Control, NORAD) • Terrorism Threats • Global Warming