Choosing the correct test

Question 1

learn this table of overview of common statistical tests

Answer 1

Question 2

what does outcome variable mean?

Answer 2

the thing you’re comparing between diff groups

Question 3

what does the type of statistical test we decide to use depending on?

Answer 3

• is the outcome continuous or binary or a time?
• the relationship of groups comparing: independent or correlated?
• consider the assumptions that need to be made

Question 4

when we have a continous outcome how do we translate this into a statistical research question?

Answer 4

Question 5

what is the outcome variable in this case?

Answer 5

maths score

Question 6

the type of outcome variable in this case is maths score. what type of variable is this?

Answer 6

contunuous

Question 7

the type of outcome variable in this case is maths score, which is a continuous variable

is it normally distributed?

Answer 7

yes - we will assume it is for the purpose of this demo example

Question 8

the type of outcome variable in this case is maths score, which is a continuous variable

it is normally distributed

are the observations correlated?

Answer 8

no - as they are randomly selected

Question 9

the type of outcome variable in this case is maths score, which is a continuous variable

it is normally distributed

the observations are correlated

are groups being compared, if so, how many?

Answer 9

yes, 2

Question 10

the type of outcome variable in this case is maths score, which is a continuous variable

it is normally distributed
the observations are independant
2 groups are being compared.

Therefore, which test should we use?

Answer 10

T-test

Question 11

Example 1: two-sample T-test

what is our first step?

Answer 11

define your hypothesis (null and alternative)

Question 12

Therefore, what is our hypothesis for this question?

Answer 12

Question 13

Example 1: two-sample T-test

what is our second step?

Answer 13

seeing the observed difference

Question 14

Example 1: two-sample T-test

what is our third step?

Answer 14

Question 15

Example 1: two-sample T-test

what is our fourth step?

Answer 15

Question 16

Example 1: two-sample T-test

what is our conclusion - do we reject the null hypothesis or not? and why?

Answer 16

Question 17

Example 1: two-sample T-test

We also look at something called a confidence interval which will be a range from a negative value to a positive value.

That is to say if a confidence interval covers 0, the result is or is not significant?

Answer 17

is not significant

Question 18

Example 1: two-sample T-test

if we had a confidence interval set to one side of 0, so it does not cover 0, what does this say about the significance of the results?

Answer 18

that the result is significant as the difference cannot be 0

Question 19

Example 1: two-sample T-test

however, in this case looking at the confidence intervals and whether or not they cover 0, what does this suggest about the significance of the results?

Answer 19

that it is not significant

Question 20

Example 2:

For this scenario we are looking at
statistical question: is there a difference in remineralisation effect between the two materials?

what is the outcome variable?

Answer 20

re-mineralisation?

Question 21

Example 2:

For this scenario we are looking at
statistical question: is there a difference in remineralisation effect between the two materials?

type of variable is it?

Answer 21

continuous

Question 22

Example 2:

For this scenario we are looking at
statistical question: is there a difference in remineralisation effect between the two materials?

is it normally distributed?

Answer 22

yes - for the purpose of this example we assume it is

Question 23

Example 2:

For this scenario we are looking at
statistical question: is there a difference in remineralisation effect between the two materials?

are the observations correlated?

Answer 23

yes - same patient/ same mouth

Question 24

Example 2:

For this scenario we are looking at
statistical question: is there a difference in remineralisation effect between the two materials?

how many sites are being compared?

Answer 24

2

Question 25

Example 2: in this case what test should we use?

Answer 25

paired t-test

Question 26

compare paired t -test to t test

Answer 26

Question 27

we have an alternatives column that says, alternatives it the normality assumption is violated (and small n) what does this mean?

Answer 27

that means when we collect our data, we assume that the data we collected is normally distributed. So then we can use paired t-test or t-test. But if the data we collect is not normally distributed, or if the sample size is extremely small (less than 10), it is better to go for non-parametric test. non-parametric means we dont calc mean score for groups anymore but we use median. the mean is a parameter from the data we collected, therefore if distribution not normal then using mean score may be misleading so better to use the median. the median is not a parameter it is just a middle value

Question 28

what do we compare instead of comparing the mean in a non-parametric stats test?

Answer 28

the median

Question 29

what is the non-parametric version of a paired t-test?

Answer 29

Wilcoxon sign rank test

Question 30

what is the non-parametric version of a t-test?

Answer 30

Mann-Whitney U test

Question 31

every parametric test has a corresponding .....-parametric test alternative

Answer 31

non

Question 32

Example 3: what stats test was used here to compare mean micronutrient intake from lunch?

Answer 32

ANOVA

Question 33

Anova is the analysis of what?

Answer 33

analysis of variance (don't worry about the algorithm)

Question 34

What type of distribution is ANOVA used for?

Answer 34

normally distributed variables

Question 35

what other test is ANOVA just an extension of?

Answer 35

Question 36

what is the null hypothesis of anova?

Answer 36

comparing more then 3 groups so null = there is no difference between the 3 groups

Question 37

what is the alternative hypothesis of anova?

Answer 37

Question 38

what type of test do ANOVA use?

Answer 38

F-test

Question 39

what does a statistically significant ANOVA (F-test) tell u about the difference between groups?

Answer 39

Question 40

does ANOVA tell u which groups differ?

Answer 40

no - just states that they do differ

Question 41

Question 42

instead of using anova, why cant we just do 2 pai-wise t-tests?

Answer 42

Question 43

what correction do we do for multiple comparisons?

Answer 43

important to understand what it is and how it is done

Question 44

what is the name of the easiest way to carry out a correction for multiple comparisons?

Answer 44

Bonferroni correction

Question 45

if normality assumtion of Anova is violated, we use non-parametric method. what is the non-parametric version of anova called?

Answer 45

Kruskal-Wallis test

Question 46

Tests for Binary/ categorical outcome Statistical question: does the proportion of people in bad dental health differ in smokers and non-smokers? what is the outcome variable?

Answer 46

bad dental health (yes/no)

Question 47

Tests for Binary/ categorical outcome Statistical question: does the proportion of people in bad dental health differ in smokers and non-smokers? what type of variable is this?

Answer 47

binary

Question 48

Tests for Binary/ categorical outcome Statistical question: does the proportion of people in bad dental health differ in smokers and non-smokers? are the observations correlated?

Answer 48

no

Question 49

Tests for Binary/ categorical outcome Statistical question: does the proportion of people in bad dental health differ in smokers and non-smokers? are groups being compared, if so how many?

Answer 49

2

Question 50

Tests for Binary/ categorical outcome Statistical question: does the proportion of people in bad dental health differ in smokers and non-smokers? are any of the counts smaller than 5? (similar to as with coninuous data, 5 is the cut-off point this time round, to use parametric version)

Answer 50

no, smallest is 11 (current smoker in good dental health)

Question 51

Tests for Binary/ categorical outcome Statistical question: does the proportion of people in bad dental health differ in smokers and non-smokers? which test should we use?

Answer 51

chi-squared

Question 52

chi squared allows u to compare proportions between how many groups?

Answer 52

2 or more groups - so any number of groups

Question 53

so based on this interpretation and p-value, what is our conclusion?

Answer 53

Question 54

what is the alternative to chi-squared if we have less than 5 cells?

Answer 54

Fisher's exact test