Unit 6

Question 1

What are sig test used for

When do we use sig tests

Answer 1

Test a claim about the value of a population parameter

Decide whether the evidence supporting a claim is likely or unlikely to happen by chance alone.

Question 2

Conditions of a 1 sample Z interval

what is it used for

Answer 2

Population proportion

SRS
n <= 10% of N
n = sample size, N = population size
Normality: n*phat >= 10 and n * (1-phat) >= 10. ‘Conditions of normality have been met’

Question 3

General formula for confidence interval

Answer 3

Confidence interval = Point Estimate +/- Margin of error

= point estimate +/- (critical val)(standard error of statistic)

Question 4

What does the margin of error describe

Answer 4

How much a value of a sample statistic is likely to vary from the value of the corresponding population paramet.er

Question 5

Factors that affect the margin of error

what is it

Answer 5

How much statistic typically varies from the parameter
Sample size - larger the sample size, smaller the margin of error

How confident we want to be in our estimate.
Lower confidence level = lower margin of error.

Question 6

Formula of margin of error

Answer 6

Critical value * Standard error of statistic

Question 7

What is the standard error

Answer 7

Estimate of the standard dev of a sampling dist of the stat

Question 8

What is the critical value

Answer 8

The absolute value of the Z score.

Question 9

How to interpret the confidence interval

Answer 9

We are C% confident that the interval from _ to _ captures the [population parameter]

Question 10

How to justify a claim using a CI

Answer 10

If all values of CI are consistent with claim - sufficient evidence
If one or more values of CI are inconsistent with claim - insufficient evidence.

Question 11

How to interpret the Confidence level (prop)

Answer 11

In repeated random sampling with the same sample size, approx C% of “C%” confidence intervals will capture the population proportion

Question 12

What is the null hypothesis

Answer 12

A claim of no difference or no change.

H0

Question 13

What is the alternate hypothesis

Answer 13

Claim we hope to support with evidence from collected data

Question 14

When is a one sample z test used

Answer 14

Test the claim about the proportion of successes

Question 15

Conditions for a one sample z test for a population proportion

Answer 15

SRS
10% condition
N*p0 and N * (1-p0) >= 10
p0 is the prop specified by H0

Question 16

General formula for tests

Answer 16

(Statistic - parameter)/standard error of statistic

Question 17

Formula for 1 sample Z test

Answer 17

phat - P0)/sqrt(p0 * (1-p0)/n)

Question 18

What is the significance level

what is it rep by

Answer 18

Alpha

Predetermined boundary value that we use to determine if a p-value is small or not small

Question 19

What do p-values indicate

What do they do

Answer 19

Observed value of test statistic would be unusual if the null hypothesis was true

Provide statistical evidence for the alternate hypothesis.

Smaller the p value - more convincing statistical evidence for the alternate hypothesis

Question 20

What happens if p-value is < alpha

What happens if p-value is > alpha

Answer 20

Reject H0. Sufficient evidence that Ha

Fail to rej H0. Insufficient evidence that Ha

Question 21

What is a type I error
what is a type II error
generally what is more consequential

Answer 21

Null hypothesis is true and is rej (false positive)
Null hypothesis is false and is not rej
Generally type II error is more consequential

Question 22

Probability of Type I error
Probability of Type II error
what is power

Answer 22

Prob of TI error = alpha
Prob of TII error = 1-power
power = probability that the test will correctly reject a false null hypothesis.

Question 23

4 factos that affect power

Answer 23

Increasing sample size
Increasing alpha
Standard of error decreases
True parameter value is further from the null

Question 24

Conditions for a 2 sample Z interval

Answer 24

Both samples are SRS
Both samples <= 10% of respective populations
Normality: 
n1*phat1 >= 10
n1* (1-phat1 >= 10
n2*phat2 >= 10
n2*(1-phat2 >= 10

Question 25

Conditions for a 2 sample Z test

Answer 25

Both samples are SRS
Both samples <= 10% of respective populations
Normality: 
n1*pc>= 10
n1* (1-pc>= 10
n2*pc>= 10
n2*(1-pc>= 10

Question 26

Conditions for all experiments

Answer 26

SRS
NORMALITY

NO INDEPENDENCE

Question 27

Formula for 2-sample-Z-test

Answer 27

(phat1-phat2)-0 / sqrt(pc(1-pc)(1/n1 + 1/n2)

Question 28

How to interpret the P value

Answer 28

Assuming Ho is true, there is a probability of getting a difference in proportions of or , by chance alone in the random assignment (random samples).