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Analysing quantitative and qualitative data (Quantitative (Analysed using…

- - - - Mean : All scores are added up and the total is divided by the number of scores.
        - S: Takes all the values into account
        - W: there are unusual scores, the mean can be 'skewed' (pulled up or down)
        - W: May be used inappropriately by having decimal places
      - Median: The central score in a list of rank ordered scores.
        - S: Not affected by extreme scores and is useful when data is ranked ordinal level data (1st, 2nd, 3rd etc)
        - W: Only focuses on position of scores and doesn't consider the values, which can be misleading in a small set of scores
      - Mode: The score that occurs most frequently in a set of nominal level scores.
        - S: Not affected by extreme scores
        - S: The only measure of central tendency that is usually appropriate to use with nominal level data
        - W: Tells us nothing about the scores and there may be more than one mode in a set of data
    - - Range : Simplest calculation of dispersion, difference between highest and lowest value.
        - W: Affected by extreme scores. If scores are extreme, better to calculate interquartile range
        - W: Does not tell if scores are bunched around mean score or equally distributed
      - Standard deviation: Calculates mean, deducts it from each score, squares number, divides by (n-1) (number of scores in set minus one), which is variance, and square root to get standard deviation
        - S: More reliable than range, discards anomalies, meant to calculate dispersion over value
    - - Graphs and charts can be used to illustrate a summary of data that has been analysed, which helps us get an overview of the key findings
      - Frequency tables and histograms
        
        Used to display number of times (frequency) data occurs
        
        Histograms = no gaps to represent continuous data rather than categorical data
      - Bar charts
        
        Used to display data like mean, median, mode, percentages or totals
        
        Axis must be properly labelled
- - - - Recording themes, patterns or trends within data
        
        Researcher identifies limited number of themes reflected in data, then develop the themes through studying the data
        
        Can be done inductively (researcher would read the qualitative data a few times to find themes without imposing their own ideas or expectations) or deductively (the researcher specifies themes they will look for before analysing the data)
      - Stages of thematic analysis
        
        Once the data is gathered, a reflective journal is started to log the process of analysis
        
        Data assembled into one document
        
        Coders are appointed, someone who doesn't know the aims of the research
        
        'Codes' developed from themes, represent the categories of themes found, which are used to analyse gathered data and search for instances where it occurs
        - Reviewed continually, and changed if necessary
        - Reflective journal checked for reliability and validity before report of the process and results are written up
      - Evaluation
        
        - S: Flexible, can be implemented in different ways
        - W: Qualitative data yields more details and meaningful information than quantitative data
        - W: Considered unscientific as themes are dependent on the subjective opinions of the researcher