213 exam 4

what is the p value

the value inside the z table

if p value < alpha

reject the null, there is sufficient evidence to support the alternative

if p value > alpha

do not reject the null, there is insufficient evidence to support the alternative

if the alt hypothesis is ≠ what do you do to the p value

multiply by 2

type 1 error

rejecting when you should not have

type 2 error

not rejecting when you should have

probability of a type 1 error

alpha , the significance level

the farther away from the mean, the MORE OR LESS likely you are able to detect a type 2 error

MORE

type 2 error depends on

the value of the true mean

how does alpha effect type 1 and type 2 error

as alpha increases, type 1 increases, and type 2 decrease
as alpha decreases, type 1 decreases, and type 2 increases

as the actual mean gets further away from the desired mean, the power of the test gets LARGER OR SMALLER

LARGER, the further away from the actual mean, the more likely you are to detect a type 2 error, so type 2 error goes down, so the power of the test increases

the power of the test

1 - B (type 2 error)

the further away from the actual mean you get, it gets EASIER OR HARDER to properly reject

EASIER, further away means type 2 error decreases, which means less not rejecting when we should have

the power of the test measures

how good you are at properly rejectingi

if you do not have the population standard deviation, which table do you use

t tables

steps for creating a hypothesis test

1. write hypothesis tests
2. determine which table to use
3. find the t/z stat using givens
4. plot on graph and shade reject region
5. calculate t/z
6. plot on graph and determine if it is in the reject region
7. write the conclusion

steps for creating a hypothesis test for variance

1. write hypothesis tests
2. use the chi-square table to find the X^2 stat value
4. plot on graph and shade reject region
5. calculate X^2
6. plot on graph and determine if it is in the reject region
7. write the conclusion

how to find the range for the p values

1. calculate the t value
2. using the v value, find the two values that the calculated t value is between on the table
3. note: if it is a two tailed test, multiply the p value ranges by 2

how to improve the power of the test

increase n, decrease variance, increase alphaty

how to calculate type 2 and power of the test

1. write hypothesis
2. calculate x bar
3. calculate z/t stat
4. type 2 = B = P(z>zstat)
5. power of the test = 1 - B