Quantitative Methods - Hypothesis Testing - p-Values and Tests of Means

Question 1

what is a p-value?

Answer 1

the smallest level of significance at which the null hypothesis can be rejected

or the probability of getting the test statistic by chance if the null is true

Question 2

what is a false positive?

Answer 2

incorrect rejections of the null hypothesis

Question 3

why is adjusted significance testing used?

Answer 3

to improve the accuracy of our conclusions (there are chances of getting false positives above the calculated probability)

Question 4

when can you reject the null in relation to p-values?

Answer 4

when the significance is greater than or equal to the p-value

Question 5

if a test was two-tailed, how do you adjust the p-value from a one-tailed test?

Answer 5

double it

Question 6

how are p-values ranked?

Answer 6

in ascending order (smallest to largest)

Question 7

when do you use a t-test stat?

Answer 7

• sample is large (>30)

- sample is small (<30) but the distribution is normal/approx normal

Question 8

when do you use a z-test stat?

Answer 8

• population is normally distributed and variance is known