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data handling and analysis - Coggle Diagram
data handling and analysis
analysing quantitative data
content analysis
enables the indirect study of behaviour by examining various forms or media eg.tv,films
statistical process that involves categorising and quantifying events and behaviour as they are recorded in a particular medium
procedure
3) return to the original data and tally the number of examples in each coding unit
4) quantitive data can be statistically analysed
2) devise checklist of clearly operationalised coding units related to research aim
5) another researcher may carry out same content analysis to check reliability of analysis
1) identify sampling method (for material being analysed eg.blog or interview transcript)
evaluation
strengths
high external validity
can be replicated as data can be retained and accessed by others
allows investigations of situations that may be unethical to create as the material may already exist
limitations
subjective as judgement needed to define categories and coding units when interpreting the material
reducing data removes detail and richness of data set
thematic analysis
qualitative technique used to identify patterns of meanings and themes in qualitative data
theme refers to any idea that occurs in the data in several occasions
procedure
2) read, reread get to know transcript well
3) identify themes (patterns of response) that emerge from the transcript
1) have a transcript of language or conversation
4) look for quotes within the transcript to illustrate each theme. these quotes support the theme
evaluation
strengths
allows investigation of new areas of interest
produces rich and detailed analysis which increases validity
limitations
highly subjective, so risk of researcher bias
lacks scientific rigour
quantitive and qualitative data
quantitative
information that can be written down with numbers
strengths- simple and quick to analyse, greater of number can be included, enhances generalisation, easy comparison
limitations- collects narrow and sometimes superficial dataset as preset answers will not necessarily reflect how people really feel about a subject, reducing validity
qualitative
descriptive information that is expressed in words
strengths- provides depth and detail, stimulates peoples individual experiences
limitations- time consuming to analyse, dependant on skills of researcher, harder to generalise
primary and secondary data
primary
strengths- data gathered specifically targets the information the researcher requires which increases validity
limitations- requires considerable planning, preparation and effort
data that has been obtained first hand by the researcher directly from the ptpts. collect specifically for the research being carried out
secondary
data that has been gathered by someone else and pre-dates the current research. not collected specifically for research being carried out
strengths- inexpensive and easily accessed requiring minimal effort
limitations- content of data may not match the researchers research aim and may be variation of quality and accuracy of data
meta analysis
process where researchers collect and collate a wide range of. previously conducted research on a specific area. this collated research is reviewed together and then the combined data is statistically analysed to provide an overall conclusion
descriptive statistics
measures of central tendency
median
strength- median less affected by extreme scores than mean
limitation- not suited to being used with small sets of data especially if containing widely varying scores
arrange scores in a set of data from lowest to highest and finding the middle score
mean
strength- makes use of all the values of data so can said to be representative of all the data collected
limitation- any rogue outliers can distort the mean making it untypical of the data set
add all the scores in a set of data together and dividing by the total number of scores
mode
strength- unaffected by extreme scores and may give idea about how often something is occurring
limitation- not useful when there are two modes (bi-modal) or more
value that is most common
measures of dispersion
range
strength- easy to calculate, takes into consideration extreme scores
limitation- only uses two scores in data set so unrepresentative of data as a whole and extreme scores could distort the range
the difference between the highest and lowest numbers
standard deviation
strength- most powerful measure of dispersion as uses every score in the data set
limitation- can only be used with a normal population, may be affected by extreme values
takes into account how spread out all of the values are from the mean. the greater the SD, the more the data is spread out around the mean. therefore, the smaller the SD the more reliable the mean
presentation/display of quantitative data
bar charts
show data I the form of categories to be compared. bar charts should be the same width and should have a gap between bars- indicating the data is discrete rather than continuous.
histograms
histograms used for continuous data. continuous scores placed along x axis (horizontal) while the frequency of these scores is shown on the y axis (vertical). no spaces between the bars as data are continuous and the width for the value of the x axis should be the same width per equal category interval
graphs
graphs are a means of 'eye balling' quantitative data and seeing the findings at a glance. a graph should clearly show the findings of a study, with a short title and clearly labelled axis'
tables
used to summarise data and often state the measures of central tendancy or dispersion
distributions
positive skew
skew is located on the right
mode is lower than the mean
negative skew
skew is located on the left
mode is higher than the mean
normal
symmetrical spread of frequency data
mean median and mode all located at highest peak
levels of measurement
ordinal
data ordered in some way such as rank order
interval between measurements not fixed
weakness- lacks precision because it is based on subjective opinion rather than objective measurement
interval
based on numerical scales that include units of equal, precisely defined size.
the most precise and sophisticated form of data as based on objective numerical scales and yields a numerical score for each ptpt
measurement of height, time, temperature, weight
nominal
data is represented In the form of categories
can only appear in one category and can be tallied
weakness- does not enable very sensitive analysis because it does not yield a numerical result for each ptpt