module 11 regression analysis

Question 1

Adjusted R2

Answer 1

• Penalises excessive use of unimportant independent variables
• example: Adjusted R2 of 0.8720 means 87.2% of the variation is explained by the variation in X1, X2, X3….Xk(all X values) considered together, taking into account the sample size and number of independent variables

Question 2

standard error

Answer 2

can be compared to the average y value

Question 3

Hypothesis

Answer 3

a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation

Question 4

Null Hypothesis

Answer 4

– a type of hypothesis used in statistics that proposes that no statistical significance exists in a set of given observations. The null hypothesis attempts to show that no variation exists between variables or that a single variable is no different than its mean

-It is presumed to be true until statistical evidence nullifies it for an alternative hypothesis.

Question 5

Alternative Hypothesis

Answer 5

– the hypothesis used in hypothesis testing that is contrary to the null hypothesis. It is usually taken to be that the observations are the result of a real effect

Question 6

Dummy variable

Answer 6

– also known as an indicator variable or quantitative variable is one that takes the value of 0 or 1 to represent a non-numerical variable e.g. smoker/non-smoker