interpreting results

Question 1

what is a p- value?

Answer 1

probability of seeing data as least as extreme as in your sample, if the null hypothesis is true.

Question 2

when, interpreting p-value when number needs to be considered?

Answer 2

0.05

Question 3

p>0.05

Answer 3

then you cannot reject the null hypothesis - there is insufficient evidence of a difference

Question 4

p<0.05

Answer 4

then you can reject the null hypothesis - you have good evidence that there is a difference

Question 5

statistical error-type I error

Answer 5

you say there is a difference but in the population there is not (a false positive)

Question 6

statistical error-type 2 error

Answer 6

you say there is no difference but in the population there is (a false negative)

Question 7

what is effect size

Answer 7

clinical or practical significance

Question 8

how is the effect size found?

Answer 8

once there is data from the research we can quantify how big a difference it is

Question 9

advantage of effect size?

Answer 9

we can compare them across different studies, even if different outcomes have been measured.

Question 10

what can the effect size be compared to?

Answer 10

“effect size needed to change someone’s mind” to decide the the effect you have found is clinically or practically significant