Stats

Question 1

Qualitative Variable

Answer 1

A non-numerical variable, like hair colour or eye colour

Question 2

Quantitative Variable

Answer 2

A numerical variable, like length, time

Question 3

Continuous variable

Answer 3

Can take any value within a given range, e.g. height, time, age,

Question 4

Discrete variable

Answer 4

Can only take certain values, e.g. shoe size, cost in £ and p, number of coins.

Question 5

What type of data do histograms deal with?

Answer 5

Continuous data –> no spaces between the bars

Question 6

Define the mode

Answer 6

The value which occurs most often.

Question 7

Define the mean average

Answer 7

Where you add up all the numbers and then divide by the number of numbers

Question 8

Define the median

Answer 8

The median is the middle number in an ordered list.

Question 9

When is the mode used?

Answer 9

You should use the mode if the data is qualitative (colour etc.) or if quantitative (numbers) with a clearly defined mode (or bi-modal). It is not much use if the distribution is fairly even.

Question 10

When is the mean used?

Answer 10

This is for quantitative data (numbers), and uses all pieces of data. It gives a true measure, and should only be used if the data is fairly symmetrical (not skewed).

Question 11

When is the median used?

Answer 11

You should use this for quantitative data (numbers), when the data is skewed, i.e. when the median, mean and mode are probably not equal, and when there might be extreme values (outliers).

Question 12

What is the range?

Answer 12

The range is the largest number minus the smallest (including outliers).

Question 13

What’s an outlier?

Answer 13

An extreme value

Question 14

Ordinal variables

Answer 14

An ordinal variable is a categorical variable for which the possible values are ordered.

Question 15

Nominal variables

Answer 15

Nominal variables have two or more categories without having any kind of natural order. They are variables with no numeric value, such as occupation or political party affiliation.

Question 16

Binary variables

Answer 16

Binary variables are variables which only take two values.

Question 17

What are the various sources of data?

Answer 17

Routinely collected data:
- Mortality and census data
- Hospital activity data
- Primary care data
- Infectious disease notifications
- Regular national surveys (e.g. Health Survey for England)
Research study data

Question 18

Continuous variables

Answer 18

Have numerical values

Measurements are on a continuous scale i.e. can take an infinite number of distinct values

Question 19

Discrete variables

Answer 19

Also known as count variables

Have numerical values, but they must be integers e.g. Number of fillings

Question 20

What are the appropriate graphical presentations to use for 1 categorical variable?

Answer 20

Bar chart
Pie chart
Frequency table

Question 21

What are the appropriate graphical presentations to use for 1 continuous variable?

Answer 21

Histogram

Bar chart

Question 22

What is the appropriate graphical presentation to use for a categorical outcome and categorical exposure?

Answer 22

Contingency table

Question 23

What is the appropriate graphical presentation to use for a numerical outcome and categorical exposure?

Answer 23

Box and whisker plot

Question 24

What is the appropriate graphical presentation to use for a numerical outcome and numerical exposure?

Answer 24

Scatter plot

Question 25

What are other terms for 'exposure'?

Answer 25

``` Explanatory variable Independent variable X variable Risk factor Treatment group ```

Question 26

What are other terms for 'outcome'?

Answer 26

``` Response variable Dependent variable Y variable Case/control group Disease group ```

Question 27

Bar charts

Answer 27

heights of the bars are proportional to the frequencies | useful for comparing the frequencies in each category relative to the others

Question 28

Pie charts

Answer 28

areas of the sectors are proportional to the frequencies | useful for comparing the frequencies in each category with the whole group

Question 29

Normal distribution

Answer 29

A distribution where the mean, median, and mode are roughly similar A probability distribution that describes data that is symmetric around a mean

Question 30

Describe positive skewness

Answer 30

Mode < median < mean | Also known as a right-skewed distribution because it has a long right tail.

Question 31

Describe negative skewness

Answer 31

Mode > median > mean | Also known as a left-skewed distribution because it has a long left tail

Question 32

Define the term 'standard deviation'

Answer 32

Measure of spread of observations around the mean

Question 33

Define the term 'interquartile range'

Answer 33

Range from first (25%) to third (75%) quartiles of a distribution

Question 34

What is a distribution?

Answer 34

* describes the frequency (or probability) of occurrence for a given value * describes the shape of the data

Question 35

What can we do with a distribution?

Answer 35

- make inferences about a wider population - generate confidence intervals (assessing variability of estimates) - test hypotheses - calculate sample size

Question 36

Define skewness

Answer 36

A measure of the asymmetry of the distribution

Question 37

What is a null hypothesis?

Answer 37

A hypothesis saying that the outcome is not associated with the exposure

Question 38

What is an alternative hypothesis?

Answer 38

A hypothesis saying that the outcome is associated with the exposure

Question 39

Why use statistical tests?

Answer 39

We use statistical tests to help us judge if our observed effect size is due to chance or if it is real.

Question 40

What is the significance level?

Answer 40

* The probability that you will find an effect that does NOT actually exist * Strength of evidence needed to reject NULL hypothesis * Normally set to 5%

Question 41

Define the term 'inferential statistics'

Answer 41

Inferential statistics allows you to make predictions (“inferences”) from that data. With inferential statistics, you take data from samples and make generalisations about a population.

Question 42

What is meant by standard error?

Answer 42

* Standard Error is an inferential statistic. | * It is an estimate of how variable a statistic would be if we repeated our study numerous times.

Question 43

What are p-values?

Answer 43

P-values give the probability that we observed an effect size as large as we did if the null hypothesis is true i.e. effect size is zero

Question 44

What do p-values tell you?

Answer 44

P-values tell us the strength of the evidence against the null hypothesis that there is no association. As the p-value decreases the evidence against the null hypothesis increases.

Question 45

What do confidence intervals tell you?

Answer 45

The confidence interval shows the range of values in which the true effect size is likely to lie. A 95% confidence interval tells us that in 95% of replicate experiments, the true value will lie in the interval.

Question 46

How can the concept of disease be influenced?

Answer 46

* Evidence of symptoms * Technological and medical development * Sociocultural environment

Question 47

Define the term 'abnormality'

Answer 47

Different from what is usual or average, especially in a way that is bad

Question 48

List the three types of abnormality

Answer 48

* Abnormal if unusual * Abnormal if associated with clinical abnormality * Abnormal if increased risk of future disease

Question 49

Abnormal if unusual

Answer 49

Common in laboratory testing to define normal as the range which includes 95% of values found in healthy subjects. This means abnormal is the top and bottom 2.5% of the population

Question 50

What's wrong with defining abnormal as unusual?

Answer 50

By definition 5% of healthy people will have “abnormal” i.e. “unusual” values

Question 51

Abnormal if associated with clinical abnormality

Answer 51

More logical to label values of a test as abnormal if these values are clearly associated with the presence of a disease state.

Question 52

What's wrong with defining abnormal as being associated with clinical abnormality?

Answer 52

There's almost always overlap between values in diseased subjects and those in healthy subjects

Question 53

Abnormal if increased risk of future disease

Answer 53

A biochemical measure in asymptomatic individual may be associated with future disease in a causal way