In statistical modeling, regression analysis helps you to:
a. None of them
b. estimate the relationships between two dependent variables and one independent variable.
c. estimate the relationships between a dependent variable and one or more independent variables.
d. calculate the exact values for the dependent and independent variables.
In statistical modeling, regression analysis helps you to: a. None of them b. estimate the relationships...
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 β 1 term indicates 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...
Regression analysis is an important statistical method for the analysis of business data. It enables the identification and characterization of relationships among factors and enables the identification of areas of significance. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls. Comment on what these pitfalls may be and how you would avoid them. Use an example if it helps to clarify the point.
regression analysis is an important statistical method for the analysis of business data. It enables the identification and characterization of relationships among factors and enables the identification of areas of significance. The performance and interpretation of multiple linear regression analysis is subject to a variety of pitfalls similar to simple linear regression. Comment on additional pitfalls when analyzing multiple factors and how you would avoid them. Use an example if it helps to clarify the point.
4 & 5 QUESTION 4 What is a major difference between linear regression and logistic regression? a. The nature of the independent variable(s) b. The nature of the dependent variable c. The number of independent variables d. The number of dependent variables QUESTION 5 Which one of the following statistical tests would the researcher hope to have a non-significant result (p > .05) in a logistic regression analysis? a. The likelihood ratio test b. The logit step test C. The...
If you perform a hypothesis test on the population slope Parameter (β1) in regression analysis and reject the Null hypothesis: Ho: β1= 0. Your conclusion would be: A.) The least squares sample regression equation should not be used because there is not sufficient evidence of a relationship between the independent variable and the dependent variable.. B.) The least squares sample regression equation should be used because there is sufficient evidence of a relationship between the independent variable and the dependent...
QUESTION 3 Which of the following statements describes why multiple regression is often a superior statistical technique over bivariate regression? If done properly, in multiple regression analysis, you get better estimates of the coefficients than you would in a bivariate regression analysis. If done properly, in multiple regression analysis, you get better estimates of the dependent variable than you would in a bivariate regression analysis. If done properly, in multiple regression analysis, you get an improved R-square and adjusted R-...
1. Which of the following is correct? A. In correlation analysis there are two variables and both are dependent B. I n correlation analysis there are two variables and both are independent C. I n regression analysis there are two variables and both are dependent D: In regression analysis there are two variables and both are independent 2. measures the strength of linear association between two variables. A. Regressor B. Regressand C. Correlation coefficient D. None 3. the independent variables....
6. Which of the following statements is correct? A. Factor analysis is a type of regression analysis predicting a categorical outcome B. In multiple regression analysis, several independent variables are used to estimate the value of an unknown dependent variable Multiple correlation analysis measures the strength of association of two variables while controlling/removing the effect of a third variable C. D. All of the above. 7. A researcher wants to assess the effect of two types of exercise regimes aiming...
In regression analysis: a. the independent variable must be categorical in nature. b. the variables being investigated must not be correlated. c. the independent variable is indisputably influenced by the dependent variable. d. one variable is believed to be influenced by the other.