W4 - Confidence Intervals & Hypothesis Testing

Question 1

Do we want a higher or lower SE?

Answer 1

Lower SE.

Question 2

How is SE calculated?

Answer 2

SD / (square root of sample size)

Question 3

What are confidence intervals (CI)?

Answer 3

Range of values between which you would expect the pop mean to sit.

95% likely to include the REAL pop mean.

Question 4

What does the width of the confident interval (CI) indicate?

Answer 4

Uncertainty about the unknown pop mean.

Question 5

What might a very wide CI indicate?

Answer 5

More data should be collected before anything can be determined.

Question 6

What type of width (bigger or smaller) would you want the CI for increased certainty?

Answer 6

Smaller width

Question 7

How is the lower boundary of 95% CI calculated?

Answer 7

Mean of sample - (1.96 x SE)

Question 8

How is the upper boundary of 95% CI calculated?

Answer 8

Mean of sample + (1.96 x SE)

Question 9

What are the 2 types of research Q?

Answer 9

Are the 2 variables related?

Are the 2 means different?

Question 10

TYPES OF RESEARCH Q

Are the 2 variables related?

What are the 2 ways of showing this?

Answer 10

Correlation (r)

Regression

Question 11

TYPES OF RESEARCH Q

What test would you use for the following type of research Q:

Are the 2 means different?

Answer 11

T-test

Question 12

What is the null hypothesis?

Answer 12

States there will be NO difference between means or NO relationship between variables

H(little 0)

Question 13

What does the alternative hypothesis (Ha or H1) state?

Answer 13

That there WILL be a difference between means or there WILL be a relationship between variables.

H(little 1)

Question 14

Can you prove that the alternative hypothesis is true?

Answer 14

no

Instead, can demonstrate that its more likely than the null hypothesis.

Question 15

What determines whether the null hypothesis is rejected in favour of the alternative hypothesis or if we fail to reject the null hypothesis?

Answer 15

Significance level + the probability values

Question 16

What are the types of alternative hypothesis?

Answer 16

Directional

Non-directional

Question 17

What is the alpha level?

Answer 17

(a.k.a significance level)

Probability of rejecting null hypothesis when it’s actually true.

i.e a significance level of 0.05 indicates a 5% risk of concluding there’s a difference when there’s no actually difference.

Question 18

How is a type 1 error (a.k.a false +ive) created in regards to the null hypothesis?

Answer 18

You conclude there’s a difference, when in reality there isn’t.

Question 19

What is the probability of making a type 1 error represented by?

Answer 19

Alpha level

Question 20

How is a type 2 error created in regards to the null hypothesis?

Answer 20

Researcher concludes there’s NO difference when there actually is.

Could happen if their sample size is too small.

Question 21

What does the p-value provide a measure of?

Answer 21

Strength of evidence vs null hypothesis.

Question 22

What does a smaller p-value mean?

Answer 22

Smaller probability that the observed difference was due to chance (unrepresentative samples)

Question 23

What happens when p=0.03?

Answer 23

REJECT null hypothesis + interpret difference as ‘real’.

Yet there is a 3% chance that the diff has occurred by chance (due to sampling variation).

Question 24

What does a smaller P value result in?

Answer 24

Stronger evidence vs the null hypothesis