DATA ANALYSIS (1) - TYPES OF DATA & LEVELS OF MEASURMENT
Qualitative Data: Recorded in a non-numerical, narrative form.
Quantitative Data: Measured on a numerical basis.
Parametric data: equal fixed units between intervals
Nominal: Naming or catgorising participant responses (E.g. ethncity, smoking status)
Ordinal: Intervals aren't the same but they're put in order (E.g hierachy 1st/2nd/3rd)
Non-Parametric data: not fixed intervals (stretched in some places, rigid in others)
Interval: 0 is an arbitary zero (E.g. clothes, size, degrees)
Ratio: 0 is an absolute zero (E.g weight, length)
DATA ANALYSIS (2) DESCRIPTIVE STATS
Mean: Cannot be used with nominal data, makes use of all values but misrepresents when affected by extreme values.
Mode: Useful with nominal data but not useful in describing when there's multiple modes
Median: Isn't as sensitive as mean because not all values are reflected in the median or affected by extremes.
Range: Provides direct information and easy to calculate but is affected by extremes
Standard deviation: More precise measure of dispersion all values are considered but can hide some characteristics of data such as extreme values.
DATA ANALYSIS (3+4) INFERENTIAL STATS.
They help you draw conclusions by applying statistical tests to the data, you are given the observed value.
To identify the critical…