3.which of the following scenarios could give you a regression analysis?
a. there is no linear relationship between the variables
b. correlation will be done after the regression analysis
c. there is a strong negative linear relationship between the variables
d. the value of r is not significant
4. In a regression line, how do you call the magnitude of the change in one variable when the other variable changes at a unit?
a. unit change
b. variable change
c. marginal change
d. regression change
5. If the equation of the regression line is y'=6+.234×, how can it be interpreted?
a. every unit of change in the value of y, the value of X also changes at 6 units on average
b. the slope of the line is .234
c. every unit of change in the value of X, the value of y also changes at .234 unit on average
d. every unit of change in the value of X, the value of y also changes at 6 units on average
a. there is no linear relationship between the variables
b. correlation will be done after the regression analysis
c. there is a strong negative linear relationship between the variables
d. the value of r is not significant
4. In a regression line, how do you call the magnitude of the change in one variable when the other variable changes at a unit?
a. unit change
b. variable change
c. marginal change
d. regression change
5. If the equation of the regression line is y'=6+.234×, how can it be interpreted?
a. every unit of change in the value of y, the value of X also changes at 6 units on average
b. the slope of the line is .234
c. every unit of change in the value of X, the value of y also changes at .234 unit on average
d. every unit of change in the value of X, the value of y also changes at 6 units on average
Add an Answer
More Questions From This User See All
Answers & Comments
Answer:
3.c
4.b
5.a
.Which of the following is not a requirement for regression analysis? The method for regression analysis line is not robust. It is seriously affected by a small departure from a normal distribution. ... Use the regression line for predictions only if the data go far beyond the scope of the available sample data.
.Consider a regression equation, Estimation whether the association is linear or non- linear this not be answered by the regression equation. Linear regression attempts to model the relationship between two variables by fitting a linear. This does not necessarily imply that one variable causes the other.
Step-by-step explanation:
pa brienliest po