Data recording, analysis and presentation (levels and types of data) Flashcards
Three. Different level of data.
Nominal
Ordinal
Interval or ratio
Definition of norminal level of data
Categories
Definition of ordinal level of data
Rank position/ order
Definition of interval or ratio data
Standard interval scales
Ratio level - true zero point (distances/time)
Interview level - can go into negative values (temperature)
Strength and weakness of nominal data
Quick and easy to obtain because it is just a headcount
Can be displayed in pie chart which can be easily made sense of
Can only analyse the mode of data and cannot calculate the mean or median
Cannot analyse measure of dispersion such as range and standard deviation
Less precise as data is grouped into categories. We don’t know how individual participants scored.
P strength and weakness of ordinal data
Can calculate mean median and mode as a measure of central tendency, so it’s more detailed
Can also calculate measure of dispersion
Can you calculate individual scores of participants and see how they differs
can be subjective as people may interpret rating scales differently
Although we can work out the range order of participant. We don’t always know the exact difference between individual scores.
More time-consuming and complex to analyse (compare to norminal)
Strength and weakness of interval or ratio data
Better than nominal
Can calculate mean median and mode measure of central tendency
Can also calculate measure of dispersion
Can you calculate individual scores of participants and see how they differ
Better than ordinal
Scores can be compare directly as precise value are recorded, you can see the actual difference between scores rather than just the rank position
The scores are more consistent as the same universal scale is used
Worse than ordinal
Can only be used with concept that are measurable through universal scales cannot be used with attitudes and opinions
Worst than norminal
More time-consuming and complex to analyse
Two types of data (Q)
Qualitative
Quantitative
Definition of quantitated data
Numerical
Definition of Qualitative data
Non-numerical
Words description, meaning pictures
Strength and weakness of quantitative data
Allowed, easy comparison and analyses
Summarise easily using average or percentage
Easier to establish the reliability of result, as we can repeat to see if finding can be replicated or not
Narrow and not detailed enough
May not reflect how we would respond in every day life , like ecological validity (we don’t normally rate feelings)
Qualitative data, strength and weakness
More detail about subject, studying
More valid
Harder to make comparison between participants response
Hard to summarise, analyse and conclude , drawn based on opinion of researcher (open Tobias)
Two types of data obtained for correlation analyses
Primary data
Secondary data
Definition of primary data, example
Data gather directly from the participants by researcher
Self-report , experiment
Definition of secondary data
Data that has already been gathered by someone other than the researcher, already exist
