When a dummy variable is included in a regression model that has one numerical independent variable, what assumption do you need to make concerning the slope between the dependent variable, y, and the numerical independent variable, x?

Step-by-step explanation:

You need to assume that the slope between the dependent Varian and the numerical independent variable is zero.

In regression analysis, to find the effect of one independent variable on the dependent variable, there has to be no interference from the other independent variables whether they be categorical (dummy) or numerical independent variables.

A dummy variable is one which takes on the value of 0 or 1, to represent the absence or presence (respectively) of a given category which is expected to influence the dependent variable.

When a dummy independent variable is included in a regression model, to know the effect of that dummy or category (e.g. day =1, night =0) on the dependent variable, the influence of the numerical independent variable has to be removed temporarily.

In a regression equation,

Y=a+bX+cK

Y is the dependent variable

a is the intercept on the vertical axis on the graph

b is the slope between the dependent variable Y and the independent numerical variable X

c is the slope between the dependent variable Y and the dummy variable K

step-by-step explanation:

i am not sure sorry : c

1. 3.4/4

2. 0.8/7

3. 0.5 x 3

4. 0.9 x 6

5. 10.8

6. 2.35

7. 0.567

8. 9.35

9. 0.02

10. 0.06

11. 0.16

12. 0.42

13. 0.63

14. 5.6

15. 8.1

16. 9.9

17. 0.28

18. 0.48

19. 0.27

20. 0.49

21. 0.45

22. 0.72

23. 0.9

24. 0.88

25. 0.75

26. 0.16

27. 0.328

28. 0.495

29. 0.72

30. 1.068