lecture 7 Flashcards
what is Multiple Linear Regression Model used for?
studying the relationship between one dependent variable and two or more independent variables simultaneously to understand how a dependent variable can be explained by aset of other variables.
what does partial regression coefficients represent for? beta i’
the change in average y for one unit change in xi, when holding all other x’s fixed.
what is confounding
A situation in which the association between an explanatory variable (e.g
exercise !”) and outcome (e.g. weight y) is distorted by the presence of another variable(e.g. hours of free time #$).
definition of confounding variable?
Confounding variables are any other variables that cause both your dependent and your main independent variable of interest.
what is coefficient of determination? r squared
how well the regression line/hyperplane approximates the real data points
goodness of fit is ______.
he goodness of fit of any statistical model describes how well it fits a set of observations
r squared function function in context of assessing association between variables and prediction.
R2 is often interpreted as the proportion of the variance in the dependent variable that is “explained” by the independent variables in
the model; R2 is often interpreted as how well the model will be able to predict values of Y based on observed values for the independent variables xi
4 assumptions for multiple regression inference
- each iv and dv is linear association. 2. residuals or error term should be approximately normally distributed. (histogram or normal p-p plot)3. homoscedasticity ( scatterplot of standarlized residuals shows no pattern) 4. independent oberservations.
The model y = 3 + 5x - 2z + 𝜖
indicates?
Question 4Select one:
a.
For every one unit increase in x, the predicted value for y increases by 5 when z is held constant.
b.
x and z are significant predictors of y.
c.
A change of 5 units in x leads to a 2 unit decrease in y.
d.
x, y and z are significantly associated
a
