A researcher is studying daily carbohydrate intake and the next ...

[kamilo84]

A researcher is studying daily carbohydrate intake and the next day's first morning Accu-Chek value. After drawing a scatter plot, the researcher develops a multiple regression equation. What does the value R represent?
 
  a. The line of best fit
  b. The amount of change in Accu-Chek values that daily carbohydrate intake predicts
  c. Daily carbohydrate intake times Accu-Chek value
  d. The correlation between daily carbohydrate intake and the next day's first morning Accu-Chek value

Question 2

A researcher is studying stress and various factors that seem to be related to it, in women with terminally ill spouses.
 
  Among other things, the researcher finds out that depression contributes to total stress; depression contributes to lack of exercise; a decreased amount of exercise contributes to depression; exercise relieves stress; guilt contributes to depression; exercise has no effect on guilt, but it affects total stress; stress worsens depression; and stress decreases motivation to perform exercise. This is an example of what problem commonly encountered in regression analyses?
  a. Multicollinearity
  b. Hazard ratio
  c. Odds ratio
  d. Predictive validity

[jjorrostieta]

Answer to Question 1

ANS: D
R is defined as the correlation between the actual y values and the predicted y values using the new regression equation. The R2 represents the percentage of variance in y explained by the predictor and is called the coefficient of determination.

Answer to Question 2

ANS: A
Multicollinearity occurs when the independent variables in a multiple regression equation are strongly correlated with one another. The presence of multicollinearity does not affect predictive power; rather it causes problems related to generalizability and the stability of the findings. The first step in identifying multicollinearity is to examine the bivariate correlations among the independent variables.