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2248 Q3 MLR
| Question | Answer |
|---|---|
| what is collinearity output from a regression model ? | refers to diagnostic information that helps detect whether two or more independent variables are highly correlated with each other |
| problem known as | multicollinearity |
| issue - high collinearity | can distort the estimates of regression coefficients and make the model unreliable |
| what is variance inflation factor ? | numerical measure used in multiple regression to detect multicollinearity |
| multicollinearity | when independent variables are two highly correlated with each other |
| VIF variance inflation factor | tells you how much the variance of a regression coefficient is increased because of multicollinearity |
| what is tolerance in a MRM ? | tolerance is a statistic that also help detect multicollinearity - just like VIF variance inflation factor |
| what is multiple regression model's model as a whole ? | refers to how well all the independent variables together explain the variability in the dependent variable |
| model as a whole | evaluates the overall predictive power and fit of entire model, not just individual predictors |
| what does it mean at least one predictor will be significant ? | referring to the result of overall F test |
| what happens when the IV's are highly correlated ? | creates a problem called multicollinearity - and can seriously affect your analysis -unstable coefficients, inflated standard errors, hard to interpret individual effects |
| if one predictor has a larger coefficient than another this means ? | it means that holding all other variables constant, a one unit increase in that predictor is associated with a larger change in the dependent variable that a one unit increase in the other predictor |
| what are standardised coefficients ? | also called beta weights and standardised beta coefficients are regression coefficients that have been adjusted to remove the effects of the scale |
| standardised coefficients allow you | to compare the relative importance of predictors, even if variables are measured in different units |
| where can we get overall model fit statistics on STATA? | in stata, you can find the overall fit statistics after running running a regression using the regress command regress y x1 x2 x3 |
| what is the null hypothesis | foundational concept in statistics default assumption, there is NO effect, no difference and no relationship between variables |
| what is the F ratio ? | stats term that comes from F test ratio of two variances, used to determine whether there are significant differences between groups, often in the context of analysis of variance ANOVA |
| F ratio | variance btwn groups / variance within groups |
| what is the regression equation ? | describes the relationship btwn a dependent variable and one or more independent variables |
| in its simplest form | when there is one independent variable the regression equation is Y = bo+b1x +e |
| what is the rvfplot for a regression model ? | RVF plot is a diagnostic tool used to evaluate the goodness of fit of a regression modl |
| rvfplot helps to check assumptions of linear regression | such as linearity, constant variance, homoscedasticity and independence of errors |
| what is homoscedasticity ? | a term used in regression analysis to describe a situation where the variance of errors (or residuals) is constant across all level of the independent variable(s) |
| in simpler terms, the spread or scatter of residuals | (the diffferences between the observed and predicted values) remains roughly the same regardless of the value of the independent variable |
| What are individual predictors ? | also known as independent variables or featuress are the variables used in a regression model to predict the value of the dependent variable (outcome) |
| each predictor represents | a factor or characteristic that may have an impact on the dependent variable. |
Created by:
brendonpizarro1