Module 1 Part 2 Descriptive Statistics Flashcards
Variable
Any characteristic of interest that is different across individuals,patients etc e.g gender, disease status
Data
Values measured for the variable
Relationship
Association between 2 or more variables
Variable types
Dependent variable
Independent variable
Dependent variable
AKA outcome, endpoint or response Caribs,e
Influence by the values of other variables
Independent variable
AKA Explanatory variable, exposure or predictor
Explains or influences dependent variable
Variable types
Data can either be continuous or categorical
Variables are also categorised by their scale of measurement
The scale of measurement is very important in determining the correct statistical techniques to sue if description and/or inference
Continuous data
Where a single observation is a number that represents an amount
A continuous variable is something that can be assessed over a range with a refined degree of measurement
AKA numerical data or qualitative data
Categorical data
Not numeric
Organises
D into categories, groups or classes
Finite number of possibilities
Scales of measurement for categorical data
- Dichotomous (binary)
- Nominal
- Ordinal
- Interval
Dichotomous or binary data
2 groups only
Groups are mutually exclusive
Eg - dead or alive, true or false, disease or no disease
Nominal data
More then an 2 groups classified by name
Groups have no order
Collectively the groups are exhaustive and mutually exclusive
Eg eye colour, religion, blood group
Ordinal Data
Same as nominal expect the groups have a natural and meaningful order
Differences between groups are not considered equal
Example - strongly agree/agreee/neutral/never
Interval data
Same as ordinal data expect that the size of the intervals between groups is equal and meaningful
Eg - 0/1/2/3/4
