(1) regression

Question 1

What is the difference between explanatory variable and response variable?

Answer 1

• Explanatory variable is the independent variable and can be controlled.
• Response variable is dependent variable as it depends on explanatory variable.

Question 2

Why may a linear regression model be suitable?

Answer 2

-If points lie in a straight line

Question 3

What is the interpretation for the b value in the form y= 0.4x+2

Answer 3

The rate of increase in y for every unit change in x.

For every unit increase in x y will increase by 0.4

Question 4

What is something that can make using linear regression models unreliable?

Answer 4

-If the value is larger than the data set this is a extrapolation.

Question 5

What happens to the PMCC in coded data?

Answer 5

-PMCC does not change

Question 6

What is a causal and spurious relationship?

Answer 6

• Causal is when the explanatory variable has a direct impact
• Spurious is when it is coincidental

Question 7

What is an r value?

Answer 7

• also known as PMCC

- The strength of the linear relationship between two variables.

Question 8

What would happen to the PMCC If a set of variables was added that does not go with the straight line?

Answer 8

-It would weaken the PMCC as it does not follow the relationship.

Question 9

why is a model y=ax^n a good model for the relationship between two variables if r=1

Answer 9

-As r is close to one graph of log(y) and log(x), supporting relationship of t=ax^n

Question 10

How do you carry out a zero correlation hypothesis test.

Answer 10

-Step 1 one tailed or two tailed. positive correlation?
(Divide sig level by two if it is a two tailed test

-Step 2, use sample size and sig level to find critical value.

-Step 3- H0: p=0
H1 p: less than or greater than p

• Step 4 see if r value falls in critical region. (greater than the critical value. Draw out number line.
• Step 5 if it falls in critical region reject H0
• Step 6 link it back to context.

Question 11

What are the two ways to use logs for linear relationships?

Answer 11

type 1 -y=ax^n

y=ab^x

Question 12

How to move from y=a+bx to coded version?

Answer 12

-sub in the coding formula for y and x

Question 13

What is the particular rule for undoing codes for mean and standard deviation?

Answer 13

As mean is average code as normal

As standard deviation is measure of spread do not add or subtract

Question 14

What is a justification of why you cannot use y=bx+c to work out value of x when y=10

Answer 14

-As the regression line is for y given x, to work out x use x on m regression line.

Question 15

What is correlation?

Answer 15

-The nature of linear relationship b between two variables.

Question 16

What do the different r values mean

Answer 16

r= -1 perfect negative relationship
r=1 perfect positive relation
r=0 perfect no linear relationship

Question 17

How do you perform a hypothesis test for zero correlation for one tailed?

Answer 17

• State h0 and h1
• Use significance level and sample size to find critical value using PMCC table
• Draw a diagram and shade critical region between CV and H+
• If r value falls in critical region reject null hypothesis.
• Conclusion in context of the question.

Question 18

How do you perform two tailed hypothesis test for zero correlation?

Answer 18

• Divide significance level by 2.

- DIagram will have h+ and h-

Question 19

How would you articulate the effect on PMCC?

Answer 19

-Would weaken/strengthen the correlation as it goes against what PMCC shows

Question 20

Why would a linear regression model be appropriate to describe f and d?

Answer 20

-because they lie on straight line.