B AD 6243: Applied Univariate Statistics Introduction to Statistical Concepts Professor Laku Chidambaram Price College of Business University of Oklahoma

BAD 6243: Applied Univariate Statistics 2 Quantitative Research Questions Descriptive: –What is the average GPA of the incoming MBA class? Difference: –Does the salary of new grads differ based on major? Relationship: –What is the relationship between gender and income in professional sports? Prediction: –Can we predict how much a manager will earn based on his education and level of experience?

BAD 6243: Applied Univariate Statistics 3 Measurement Issues What is measurement? –Mapping from one set to another –Involves instruments and attributes Attributes of good measures –Reliability –Validity –Comparability –Objectivity –Quantifiability

BAD 6243: Applied Univariate Statistics 4 Types of Variables Categorical/Nominal –Values have no intrinsic meaning (e.g., 1=Democrat; 0=Republican) Ordinal –Rank ordering (e.g., “seed” in Wimbledon) Interval –Equal distance in scales means equal distance in property being measured (e.g., years, grades) Ratio –Values represent equal amounts from an absolute zero (e.g., height, weight etc.)

BAD 6243: Applied Univariate Statistics 5 Inferential Statistics PopulationSample Population parameters Sample statistics μσσ2ρμσσ2ρ xss2rxss2r More random the sample, more generalizable the results Larger the sample, more precise the estimate of the population parameter

BAD 6243: Applied Univariate Statistics 6 Modeling Issues What is a model? Fit: Statistical model represents observed data well Abundance of linear models Models: Relations among variables –Magnitude of effect (strength -> part of overall available differentiation that is common) –Significance of effect (sample size)