Question 1 (1 point) ANOVA can be used to find the relative effects of factors o

Question

Question 1 (1 point)

ANOVA can be used to find the relative effects of factors on the dependent variable?

Question 1 options:

Question 2 (1 point)

Regression models can be used to quantify the effects of independent variables on the dependent variable?

Question 2 options:

Question 3 (1 point)

The ANOVA and Regression analyses have different goals. The main difference between both is

Question 3 options:

Independent variables are discrete or categorical in both

Independent and dependent variables are continuous

Independent variables are categorical and dependent variable is continuous in ANOVA and both are continuous in Regression analysis.

All of above

Question 4 (1 point)

In Non-linear regression model, dependent variable is a linear function of an independent variable?

Question 4 options:

Question 5 (1 point)

Multiple linear regression model has the following characteristics:

Question 5 options:

One independent variable

Multiple independent variables which are independent of each other

Multiple dependent or correlated independent variables

All of above

Question 6 (1 point)

Coefficient of determination (R2) is a measure that shows how much variance, in the data is, explained by the regression model?

Question 6 options:

Question 7 (1 point)

F-test in regression analysis shows that the model is statistically significance or insignificance?

Question 7 options:

Question 8 (1 point)

Some of non-linear model forms can be linearized by transforming the variables and linear regression analysis can be conducted to estimate the model parameters?

Question 8 options:

Question 9 (1 point)

In multiple regression analysis, the following statistical test can be conducted to determine the statistical significance of independent variables?

Question 9 options:

F-test

t-test

z-test

None of above

Question 10 (1 point)

Total sum of squares (SSE) is an estimate of total variance in the data?

Question 10 options:

Please help!

Explanation / Answer

1) ANOVA can be used to find the relative effects of factors on the dependent variable. So the given statement is True. (Ans).

2) Regression models can be used to quantify the effects of independent variables on the dependent variable. So the given statement is True. (Ans).

3) Independent variables can be discrete or categorical, or continuous in both ANOVA and regression. Here all the given statements are true. (Ans).

4) In Non-linear regression model, dependent variable is a non-linear function of an independent variable. So the given statement is False. (Ans).

5) Multiple linear regression model has: Multiple independent variables which are independent of each other. So, 2nd Option is the correct choice. (Ans).

6) Coefficient of determination (R2) is a measure that shows how much variance, in the data is, explained by the regression model. So the given statement is True. (Ans).

7) F-test in regression analysis shows that the model is statistically significance or insignificance. So the given statement is True. (Ans).

8) Some of non-linear model forms can be linearized by transforming the variables and linear regression analysis can be conducted to estimate the model parameters. So the given statement is True. (Ans).

9) In multiple regression analysis, t-test can be conducted to determine the statistical significance of independent variables. So, 2nd Option is the correct choice. (Ans).

10) Total sum of Squares (TSS) is an estimate of total variance in the dataset. MSE(SSE/d.f.) is an estimate of the error sum of squares. So, the given statement is True. (Ans).

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