An analyst construcs the following: Ho: b=0 H1: b>0 The null hypothesis means: A) The dependent variable is sensitive to changes in the independent variable B) The independent variable is sensitive to changes in the dependent variable C) Changes in the dependent variable do not explain changes in the independent variable D) Changes in the independent variable do not explain changes in the dependent variable
The answer is D but the question is weird. I assume the question is about linear regression, b = 0 means correlation = 0 which means that dependent variable has no correlation to the independent variable.
Y = b0 + b1X
Dinesh, I think you’re missing the error term. Doesn’t the error term affect the Dependent variable too? Maratikus. I went with D too, but the correct answer is C. :S
kevin, their correct answer is wrong. it’s always independent variable that is supposed to explain dependent variable.
I agree with maratikus. The null hypothesis is stating there is no correlation between the dependent and independent variable. Correlation is measuring explainable change in dependent variable for change in independent variable. D.
Definitely D, don’t care what the answer key says. The fact that changes in the IV (the variable manipulated) do not explain changes in the DV (the measured variable) is a proponent of the null hypothesis
is D, the question here is describing beta one as “b”. So the null says that the independent variable “b” does not explain the variation in the dependable variable y.