Analysis of data: tables (quantitative) and thematic analysis (qualitative), (SP)

Question 1

Quantitative: frequency tables
what is it?

Answer 1

A frequency table shows how many times (the frequency) the scores occurred in a data set.

Question 2

Quantitative: summary table
what is it?

Answer 2

Summary tables represent measures of central tendency and dispersion clearly for number of cups of coffee consumed by males and females

Question 3

Quantitative: graphs
what is it?

Answer 3

Bar charts are used to present data from a categorical variable such as the mean, median or mode. The categorical variable is placed on the x-axis and the height of the bars represents the value of that variable. The bars on a bar chart have space in between to indicate categorical (discrete) data is being used.

Question 4

Qualitative: thematic analysis
what is it?

Answer 4

Qualitative data is non-numerical. It can be gathered through interviews, questionnaires, case studies and observations. Thematic analysis is a technique for analysing this qualitative data but without losing its meaningfulness. It allows psychologists to reduce large amounts of qualitative data into general patterns, trends and themes

1) Read the text carefully and identify any themes that appear frequently or appear to be important
2) Identify any categories within the themes eg positive/negative. These are classed ‘codes’
3) Analyse the data using the codes. This may just involve counting how many times each code occurs or the researcher could just pick quotes which demonstrate the main themes.
4) The process is reviewed and the codes are adapted and refined until the themes can be stated, supported and used to summarise the data.

Question 5

What does inductive mean?

Answer 5

the researcher would read, and re-read the qualitative data gathered and themes would emerge from the data without the researcher imposing any of their own ideas or expectations from it.

Question 6

What does deductive mean?

Answer 6

the researcher specifying the themes that they will look for before analysing the data.

Question 7

strengths and weaknesses

Answer 7

Strengths:
- A way of reducing a large amount of data into a manageable summary and conclusion, without losing validity of the data, if the analysis is done well.
- If inductive approach taken it encourages the researcher to derive themes from the data, rather than impose pre-selected themes, which is likely to be more valid
- Don’t need to learn a complex mathematical algorithm to be able to conduct this analysis.
- The results can be reduced to quantitative form.

Weaknesses:
- It is phrase-based and sometimes phrases cannot capture the meaning correctly.
- It is subjective, there might be researcher bias.
- Validity might be particularly affected if deductive approach taken, as themes will be imposed onto the data.
- Time consuming method of analysis as you have to think of how to categorise codes together and identify patterns to create a limited number of themes.