a. |
the Y value for a given value of X. |
|
b. |
the average change in Y for a unit change in X. |
|
c. |
the Y value when X equals zero. |
|
d. |
the change in observed X for a given change in Y. |
What does regression analysis attempt to establish?
a. |
linearity in the relationship between independent variables |
|
b. |
a mathematical relationship between a dependent variable, for which future values will be forecast, and one or more independent variables with known values |
|
c. |
multicollinearity |
|
d. |
linearity in the relationship between a dependent variable and a set of independent variables |
a. |
regression sum of squares. |
|
b. |
total sum of squares. |
|
c. |
correlation coefficient. |
|
d. |
coefficient of determination. |
a. |
for examining linear trend data only. |
|
b. |
for capturing uncertainty in predicted values of Y. |
|
c. |
that assumes all data is normally distributed. |
|
d. |
for analyzing the relationship between dependent and independent variables. |
|
a. |
R2 |
|
b. |
adjusted R2 |
|
c. |
partial R2 |
|
d. |
total R2 |
|
a. |
1 |
|
b. |
2 |
|
c. |
3 |
|
d. |
4 |
Ans:
1)The β 1 term indicates the average change in Y for a unit change in X.
2)Regression analysis attempt to establish
linearity in the relationship between a dependent variable and a set of independent variables
3)R 2 is also referred to as coefficient of determination.
4)Regression analysis is a modeling technique for analyzing the relationship between dependent and independent variables.
5)goodness-of-fit measure is commonly used to evaluate a multiple regression function is
R^2
Option a is correct.
6) Number of independent variables are there in simple regression analysis=1
Option a is correct.
Regression analysis (also known as predictive analytics) attempts to establish: multicollinearity linearity in the relationship between independent variables multiobjectivity a mathematical relationship between a dependent variable, for which future values will be forecast, and one or more independent variables with known values linearity in the relationship between a dependent variable and a set of independent variables
The following information regarding a dependent variable (Y in $1000) and an independent variable (X) is provided. Y Dependent Variable 15 17 23 17 I. The least-squares estimate of the slope equals: II. The least-squares estimate of the intercept equals: III. If the independent variable increases by 2 units, the dependent variable is expected to a. decrease by $300 b. decrease by $3000 c. decrease by $3 d. decrease by $2 e. none of the above The letter corresponding...
The following information regarding a dependent variable (Y in $1000) and an independent variable (X) is provided. Y Dependent Variable 15 17 23 17 I. The least-squares estimate of the slope equals: II. The least-squares estimate of the intercept equals: III. If the independent variable increases by 2 units, the dependent variable is expected to a. decrease by $300 b. decrease by $3000 c. decrease by $3 d. decrease by $2 e. none of the above The letter corresponding...
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game thory ,hst the cofficien of ltemination cqual? A) 0.1945 B) 0.4225 C) 0.5778 D) 0.8061 45. The hypothesis to test the slope of a regression equation is Ho: a 0 TRUE FALSE 46. The least squares technique minimizes the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y TRUE FALSE 47. The regression equation is used to estimate a value of the dependent variable Y based ona selected value...