L2

Question 1

population

Answer 1

is the fun set of units to which the study results will be generalised

Question 2

sample

Answer 2

the subset of the population that has been selected/ sampled to participate in the research study

Question 3

data

Answer 3

are information collected from sample units e.g. blood pressure

Question 4

the population is usually

Answer 4

infinite in size- all units that exit and ever will exist are relevant to study questions

Question 5

uncertainty about the true answer is due to

Answer 5

• variability between people in which you are trying to measure
• the sample is only a subset of the pop. and is not perfectly representative of it

Question 6

stats ar eisend to

Answer 6

summarise data in the sample and quantify the uncertainty in the sample results

Question 7

descriptive stats methods

Answer 7

describe and summarise data samples e.g. how common are certain characteristics and how diff characteristics are associated with eachother

Question 8

inferential stats methods

Answer 8

use sample data to make inferences about characteristic and relationships in the pop.

Question 9

SE and CI

Answer 9

estimation

Question 10

P values

Answer 10

hypothesis testing

Question 11

Standard eror

Answer 11

how close is the estimate to the truth
- indicates how far on average the same estimate i expected to be from he true population parameter value, if you did the study many times with diff samples of the same size

Question 12

what does SE indicated

Answer 12

If we did the study a large number of times with different samples of the same size then, on average, our sample estimates would be 0.6 units away from the true mean difference. It doesn’t mean that the estimate we have in our study is 0.6 units from the truth

Question 13

SE quantities the

Answer 13

precision of the estimate

Question 14

the smaller the SE

Answer 14

the closer the estimate to the true value in the population

Question 15

larger the sample size the

Answer 15

smaller the SE

Question 16

diff between SE and SD

Answer 16

SE summarises the precision of the estimate from a research study but standard deviation summarises the variability of observations within the sample for a quantitative variables.

Question 17

hypothesis testing can only be used

Answer 17

to provide evidence about what the true answer is

Question 18

why are confidence intervals more useful

Answer 18

since they tell you something about what the true answer in the population is

Question 19

relationship between 95% CI’s and p-value

Answer 19

can be used to carry out a test of the null hypothesis at the 5% level of significance

Question 20

if the 95% CI includes the null hypothesis then p value is

Answer 20

larger than 0.05

Question 21

if the 95% CI excludes the null hypothesis then p value is

Answer 21

smaller than 0.05

Question 22

if the lower limit of the 95% CI is the same as the null hypothesis value then

Answer 22

p= 0.05

Question 23

CI represents the

Answer 23

true parameter value

Question 24

we cannot draw any conclusion about the population based on just the mean diff between the intervention and control groups in the sample depressions core so…

Answer 24

we use inferential stats methods to tell us something about the truth in the population

Question 25

if the mean depression score in intervention group is 1.3 lower than the control group, what would a 95% CI of 0.1 to 2.4 tell us

Answer 25

we are 95% certain that in the population of infant with sleep problems at 7 months the mean maternal depression score at 12 months is somewhere between 0.1 and 2.4 units lower for the intervention group than the control group

Question 26

CI is the

Answer 26

range of value within which we can be certain with some degree of confidence that the true population parameter lies- 95% confident that true answer lies within this parameter

Question 27

With Confidenc intervals it is better to

Answer 27

• have narrow CI

- better to have 95% CI than 90%

Question 28

a larger sample size will provide a

Answer 28

narrower CI

Question 29

CI are more

Answer 29

informative than SD

Question 30

Hypothesis testing

Answer 30

using p values
-estimate is our estimate consistent with the null hypothesis we construct a statement about the ‘true’ parameter value (null hypothesis)

Question 31

a p-value of 0.03 indicates

Answer 31

moderate evidence that there is a significant difference between the groups

Question 32

the null hypothesis

Answer 32

the most boring truth imaginable

- not necessarily what you think the truth is

Question 33

example of null hypothesis

Answer 33

mean systolic blood pressure in diabetics is the same as in the general, healthy population

Question 34

the smaller the p value

Answer 34

the more evidence that the null hypothesis is false

Question 35

traditionally 0.05 has been used as the threshold to reject or not reject the null hypothesis.

Answer 35

if the p<0.05 then reject null hypothesis- significant evidence strict adherence is not recommended (not much diff between 0.049 and 0.051

Question 36

summary SE

Answer 36

how close might our sample estimate be to the true answer

Question 37

summary CI

Answer 37

what IS the answer

Question 38

hypothesis testing summary

Answer 38

what isn’t the answer