BUAD 310: Final Exam Study online at https://quizlet.com/_5rrk1n 1. Correlation What does r in between (-1 - 1) mean? Difference between Correlation and Causation A measure of the relationship between two variables -1= Strong Negative Correlation 0= No relationship between x and y +1= Strong Positive Correlation Correlation doesn't mean the change in one variable is a result of another one. Causation means one variable is directly affected by another. 2. Simple Linear Regression regression analysis that shows relationship between X and Y variables 3. X Variable Y Variable X= Independent and Explanatory Variable Y= Dependent and Response Variable 4. Ordinary Least Squares (OLS) - What does this do? - What does it minimize? - What do OLS Formulas produce? - What point does the OLS regression line always pass through on a scatter plot? Estimates coefficients of Slope and Intercept to ensure best fit 5. Multiple Linear Regression regression analysis that shows relationship between multiple independent X variables and a dependent Y variable Minimizes Residuals OLS Formulas produce unbiased and consistent estimates of slope and intercept The OLS Reg. Line always passes through x(bar), y(bar) 6. What is 5? Random Error What does it represent? How is it distributed? Represents everything not included in the model Is it observed? What type of Variance? Normally Distributed Are they independent? 1/4 BUAD 310: Final Exam Study online at https://quizlet.com/_5rrk1n Unobservable Constant Variance Independent 7. How do the Population Slope and Intercept relate to Slope and Intercept of Least Square Line Utilize the Slope and Intercept of the Least Squares Line to obtain an accurate estimate of the Population Slope and Intercept which reduces residuals making it a better fit 8. Residual Plot - What does it tell us? - What does the fan-out pattern mean? - What does the curved pattern mean? If points are randomly dispersed around the x axis, then a linear regression model is appropriate for the data Fan out pattern means increased residual variance Curved pattern means nonlinear 9. ANOVA Table A table used to summarize the analysis of variance computations and results. It contains columns showing the source of variation, the sum of squares, the degrees of freedom, the mean square, and the F value(s). 10. What is the St. Dev. of the The Population St. Dev. Error Term? 11. What is the Standard Er- Overall measure of model fit ror? What does a Standard Er- =0 means Perfect fit aka. strong correlation ror = 0 mean? 12. Variation Around Mean of Y - What is SST, SSR, and SSE - What does a good and perfect fit look like? SST= Total Variation around the mean of Y SSR= Explained Variation in Y which is difference between conditional and unconditional mean SSE= Unexplained Variation in Y 2/4 BUAD 310: Final Exam Study online at https://quizlet.com/_5rrk1n Good Fit= SSE<SST Perfect Fit= SSE= 0 = conditional=unconditional mean 13. How do you solve issues of Heteroscedasticity (Non-Constant) in Residual Graphs? Transform X and Y by taking Logs 14. What happens to Rsquared when a new explanatory variable is added to a regression? It increases because in a regression, the errors are minimized thus maximizing rsquared. Therefore, when you increase k, the quality of the fit is improved thus increasing rsquared. 15. Adjusted Rsquared What does it get rid of? What does a small/large gap mean between rsquared and adj. rsquared? Add additional predictors to increase rsquared Gets rid of useless predictors Small Gap: Parsimonious Model- model with no useless predictors Large Gap: Lean model obtained without losing predictive power 16. F-Test Test regression for significance - What is it? - What does it compare? it compares explained variation in Y (SSR) and unexplained variation in Y (SSE) 17. Multicollinearity - What is it? - What does it cause? - How to mitigate its effects? X's are intercorrelated instead of being independent Variance Inflation - Results in wider cond. interval - Makes T Stat. less reliable Use Variance Inflation Factor (VIF) - Tests for multicollinearity in a model - If X is independent, its VIP=1 and R=0 3/4 BUAD 310: Final Exam Study online at https://quizlet.com/_5rrk1n - The larger the VIP, the more the predictor shouldn't be in the model 18. Normal Distribution Characteristics Symmetrical Unimodal 68% of Data Within 1 SD of Mean 95% of Data Within 2 SD of Mean 99.7% Data Within 3 SD of Mean 19. Robust: Definition Strength of a model, statistic, etc. 20. Central Limit Theorem The sampling distribution of the mean of any variable will be normal 21. Population Proportion Fraction of pop. with certain characteristic - What is it? - What is used to estimate Sample Proportion it? 22. Standard Error Of Sample Mean Standard Error Of The Sample Proportion the standard deviation of the distribution of sample means 23. 1 Tailed Vs. 2 Tailed Tests 1 Tailed: Determine differences amongst groups in a specific aspect 2 Tailed: See if there is difference in between groups being compared 24. Type 1 and 2 Errors Type 1: Rejecting Null when it's true Type 2: Failure to reject Null when its false 4/4
