inferential statistics

Question 1

what are inferential statistics?

Answer 1

the use of mathematics probability to tell us whether we can accept or reject the null hypothesis

Question 2

when we accept the null hypothesis…

Answer 2

are results are not statistically significant, the results could simply be due to chance alone (fluke result)

Question 3

when we reject the null hypothesis…

Answer 3

our results are statistically significant and unlikely to be due to chance alone (not a fluke, due to something we have done e.g manipulating the IV)

Question 4

how is a statistically significant results expressed?

Answer 4

in terms of probability (p)

Question 5

p < 0.05
means …

Answer 5

the probability of the results of an experiment being due to chance alone is less than 5%

Question 6

if p < 0.05, we can

Answer 6

reject the null hypothesis, as probability of it being down to chance is less than 5%

Question 7

p > 0.05
means…

Answer 7

probability of the results of an experiment being due to chance alone is more than 5%

Question 8

if p > 0.05, we can

Answer 8

accept the null hypothesis, as probability of it being down to chance is more than 5%

Question 9

if it is significant we write

Answer 9

p < 0.05

Question 10

if it is not significant, we write

Answer 10

p> 0.05

Question 11

what is a type 1 error?

Answer 11

a false positive

Question 12

what happens on a type 1 (false positive) error?

Answer 12

we would reject the null hypothesis and wrongly accept the alternative hypothesis when we should not have done so

Question 13

when do you run the risk of a type 1 error?

Answer 13

if we were less strict and accepted the significance at the p < 0.1 level (90/10)

Question 14

what is a type 2 error?

Answer 14

a false negative

Question 15

what happens at a type 2 (false negative) error?

Answer 15

we would wrongly accept the null hypothesis, and reject the alternative hypothesis when we should not have done so

Question 16

when does type 2 errors occur?

Answer 16

if we were stricter and insisted on p < 0.01 to demonstrate significance (99/1)

Question 17

how many inferential statistical tests?

Answer 17

8

Question 18

criteria for using inferential tests

Answer 18

1. are we looking for a difference or a correlation?
2. what level of data are we using (nominal, ordinal or interval) ?
3. what experimental design are we using ( IMD, RMD, correlation) ?

Question 19

mnemonic for inferential tests

Answer 19

carrots - c - chi squared
should - s - sign test
come - c - chi squared
mashed - m - mann whitney U test
with - w - wilcoxon T Test
swede - s - spearman’s rho
under - u - unrelated T Test
roast - r - related T Test
potatoes - p - pearson’s r

Question 20

draw the decision table for inferential test

Question 21

what goes across the top for the decision table for inferential tests

Answer 21

level of measurement/design
IMD RMD correlation

Question 22

what goes down the column for the decision table for inferential tests

Answer 22

level of measurement/design
nominal
ordinal
interval

Question 23

what are the 3 parametric tests?

Answer 23

interval level
- unrelated T Test
- related T Test
- pearson r’s

Question 24

criteria for using a parametric test?

Answer 24

1. the standard deviation is not significantly different
2. data is normally distributed
3. data needs to be interval or ratio

Question 25

what are the non-parametric tests?

Answer 25

• chi squared
• binomial sign test
• mann-whitney U test
• wilcoxon T Test
• spearman’s rho