AS Psychology: Research Methods - Quantitative and Qualitative Data

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as level Psychology - research methods Flashcards on AS Psychology: Research Methods - Quantitative and Qualitative Data, created by Beth Strain on 12/04/2015.
Beth Strain
Flashcards by Beth Strain, updated more than 1 year ago More Less
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MEASURES OF CENTRAL TENDENCY Mean (Statistical Average) PROS: Takes all scores into account CONS: Can be distorted by extreme scores
MEASURES OF CENTRAL TENDENCY Median (Middle Value) PROS: Unaffected by extreme scores = gives a representative value CONS: Less sensitive = doesn't take all values into account
MEASURES OF CENTRAL TENDENCY Mode (Most Frequent) PROS: Useful in categorical data (e.g - no of babies securely attached) CONS: Not useful to describe data when there are several modes
MEASURE OF DISPERSION Range (Smallest score taken away from the Largest) PROS: Easy to calculate CONS: Range can be distorted by extreme scores
MEASURE OF DISPERSION Standard Deviation (Measure of dispersion that indicates the spread of data around a central value) PROS: Takes account of all scores; Sensitive measure of dispersion CONS: More difficult to calculate compared to range
MEASURE OF DISPERSION Standard Deviation Types Large S.D - A lot of variation around the mean Small S.D - Data 'closely clustered' around the mean Zero S.D - All data values were the same
Histogram Continuous Scale: Bars are joined together and are of identical width Commonly used to show scores (e.g - tests)
Bar Chart Has one data series = simple Can represent frequencies of single statistics (e.g - mean of a sample) Discontinuous (aren't joined together) Likely to be used when comparing groups of data.
Scattergram Used to show strength and relationship of correlations Can be either positive, negative, or without correlation The correlation is determined with a line of best fit. (+0.99 = STRONG POSITIVE -0.64 = STRONG NEGATIVE)
Content Analysis (Converts qualitative data into quantitative) 1) Sampling 2) Creation of Coding System 3) Pilot Study Conducted 4) Conduct the Analysis 5) Make into quantitative display 6) Check reliability (compare results)
Content Analysis (Pros & Cons) PROS: Very simple and relatively quick method of the analysis of qualitative data CONS: Can be interpreted differently by different researchers
Pure Qualitative Analysis Data is transcribed Data is read through repeatedly to detect recurrent themes All data read and re-read until all emerging themes have been identified (that account for all data collected)
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