Flashcards in Interpreting Data Deck (50):

1

## What are the two main types of data?

### Qualitative and quantitative

2

## What are the two types of quantitative data?

### Discrete and continuous

3

## What are the two types of qualitative data?

### Nominal (unordered) and ordinal (ordered)

4

## What is nominal data split into?

### Binary and categorical

5

## What is the median?

### Middle value when values ordered from smallest to largest

6

##
What is the median?

2, 3, 6, 7, 10, 11, 14

### 7

7

## What is the mode?

### Most common value

8

## What is the mean?

### The average. It is the sum of all the values divided by the number of values.

9

##
Calculate the mean.

2, 3, 4, 7, 8, 8, 11

### 6.1

10

## What does standard deviation mean?

### The average distance from the mean

11

## How is standard deviation calculated?

### The sum of (each individual value - mean) squared, then divided by the number of values. Then you square root this answer.

12

## What centile is the median?

### 50th

13

## What is the interquartile range?

### 25th to 75th centile

14

##
When is it better to use a median rather than a mean?

### To avoid the influence of outliers, i.e. if there is an outlier that is very different to the rest of the data.

15

## When is it better to use IQR rather than the standard deviation?

### To avoid the influence of outliers

16

## What is the Gaussian distribution determined by?

### Mean and standard deviation

17

## If the mean is reduced from 120 to 110, what happens to the Gaussian distribution?

###
It shifts to the left.

18

## If the mean is increased from 120 to 130, what happens to the Gaussian distribution?

###
It shifts to the right.

19

## What happens to the Gaussian distribution if the standard deviation is decreased from 15 to 10?

###
The curve becomes narrower and taller

20

## What happens to the Gaussian distribution if the standard deviation is increased from 15 to 20?

### The curve becomes wider and flatter

21

## What is a useful property of Gaussian distributions?

### A constant proportion of values will lie within any specified number of Standard Deviations above or below the mean (reference ranges).

22

## If you go one standard deviation away from the mean, how many % does this represent?

###
68%

23

## If you go 1.64 standard deviations away from the mean, how many % does this represent?

### 90%

24

## If you go 1.96 standard deviations away from the mean, how many % does this represent?

### 95%

25

## What is the 99% range? How is it calculated?

###
0.5th centile to 99.5th centile

Mean +/- 2.58 SDs

26

## What is the 95% range? How is it calculated?

###
2.5th centile to 97.5th centile

Mean +/- 1.96 SDs

27

## What is the 90% range? How is it calculated?

###
5th centile to 95th centile

Mean +/- 1.64 SDs

28

## If the sample size isn't too small then the distribution of the sample mean will be...?

###
Gaussian

29

## What is the standard error?

### The standard deviation of this distribution (Gaussian) is called the standard error. It is a measure of the statistical accuracy of an estimate.

30

## What is the standard error of the mean?

### The standard deviation of the distribution of all possible sample means – can’t do this in practice, so it is estimated.

31

## How is standard error of the mean estimated?

### Standard deviation divided by the square root of the sample size.

32

## How is the 95% confidence interval of a sample mean calculated?

###
95% CI = sample mean +/- (1.96 x standard error)

33

## What does the 95% confidence interval mean?

###
We would expect 95% of samples of the same size to have a mean between the two values calculated.

In the population we are 95% sure that the mean could be as low as ___ or as high as ___.

34

## When calculating confidence intervals and ranges, what should be used for each?

###
Standard deviation for ranges

Standard error for intervals

35

## When the sample size increases, the 95% range…

### Stays the same

36

## When the sample size increases, the 95% confidence interval…

### Gets narrower

37

## What is ‘r’? What two values is it always between?

###
Correlation coefficient

-1 and 1

38

## What does r=1 tell you?

### Perfect positive correlation

39

## What does r=-1 tell you?

### Perfect negative correlation

40

## What does r=0 tell you?

### No correlation

41

## What is the equation for a linear regression?

###
y = a + bx,

where y is the outcome and x is the predictor

42

## What does the line of best fit do?

### Minimises square of vertical distances

43

## Regression - whatever we are predicting, should it be on the vertical or horizontal axis?

### Vertical

44

## Statistical significance - what does this mean and how is it determined?

###
An observed sample difference between groups might be due to chance. Statistically significant means the result is unlikely to be due to chance.

Use confidence intervals and p-values

45

## What does a p-value mean?

### A p-value for a result is the probability of observing a result as or more extreme than the sample result if the underlying assumption in the population is true.

46

## What does the p-value have to be less than to be statistically significant?

### <0.05

47

## When can p-values be calculated?

###
When there is a comparison:

2 means – are they different i.e. is their difference different from 0?

Association – are the observed results different from those expected

Regression – is the slope different from 0?

48

## How are p-values calculated?

### Using chi-squared test

49

## If the 95% CI for a difference excludes 0 then what can be said about the p-value?

###
p<0.05

50