# RESEARCH METHODS (Part5/5) (Types of data & levels of measurement, Descriptive stats, Inferential stats, Qualitative analysis)

• Created by: Shruti
• Created on: 18-04-13 15:40

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

## Similar Psychology resources:

See all Psychology resources »See all Data analysis resources »

# RESEARCH METHODS (Part5/5) (Types of data & levels of measurement, Descriptive stats, Inferential stats, Qualitative analysis)

• Created by: Shruti
• Created on: 18-04-13 15:40

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

## Similar Psychology resources:

See all Psychology resources »See all Data analysis resources »