content and meta analysis, primary+secondary data

Question 1

what is content analysis

Answer 1

• an indirect form of observation that examines forms of media that people produce
• technique for systematically analysing various kinds of qualitative data
• data is placed into categories and counted using coding, or data is analysed in themes using thermatic analysis

Question 1

what is coding

Answer 1

• categorising data when data sets are too large when they need to be analysed
• produces quantitative data

Question 2

what is thermatic analysis

Answer 2

• process that involves the identification of themes that are recurrent
• produces qualitative data

Question 3

strengths of content analysis

Answer 3

• gets around ethical issues in psychological research as much of the material studied already exists within the public domain so no need to obtain permission
• high external validity
• flexible- qualitative and quantitative data

Question 4

weaknesses of content analysis

Answer 4

• people are studied indirectly so the communications they produce are analysed outside of the context within which it occurred. Researcher may attribute opinions which the speaker did not intend originally
• lack of objectivity when descriptive forms of thermatic analysis are employed

Question 5

what is test-retest reliability

Answer 5

• psychologist conducts content analysis
• repeats content analysis on a second occasion using the same data and same categories at a later date
• compare the 2 sets of data and look for agreement (+0.8+ correlation means it’s reliable)

Question 6

meta analysis

Answer 6

• process of combining findings from studies on a particular topic
• aim is to produce a statistical conclusion based on a range of studies

Question 7

effect-size

Answer 7

the dependent variable of meta-analysis which gives an overall statistical measure of difference or relationship between variables across a number of studies

Question 8

primary data

Answer 8

information that has been obtained first-hand by a researcher for the purposes of a research project

Question 9

secondary data

Answer 9

information that has already been collected by someone else and pre-dates the current research project

Question 10

quantitative data strengths/weaknesses

Answer 10

strengths
- simple to analyse so comparisons can be easily drawn
- numerical data is more objective and less open to bias
weaknesses
- much narrower in meaning and detail
- may fail to represent ‘real life’

Question 11

qualitative data strengths/weaknesses

Answer 11

strengths
- richness in detail as participant can fully report their thoughts/feelings
- higher external validity as there is a more meaningful insight into the participant’s worldview
weaknesses
- difficult to analyse as it isnt summarised statistically
- conclusions rely on subjective interpretations of the researcher which may be bias
-

Question 12

meta analysis strengths/weaknesses

Answer 12

strengths
- larger, more varied sample so results can be generalised across larger proportions, so higher validity
weaknesses
- publication bias where researcher may not select all relevant studies, may leave out studies with negative results, so meta analysis conclusions are biased as they only represent some of the relevant data

Question 13

primary data strengths/weaknesses

Answer 13

strengths
- authentic data obtained from the participants themselves for the purpose of an investigation
weaknesses
- time and effort for researcher
-conducting experiments requires planning, preparation, resources

Question 14

secondary data strengths/weaknesses

Answer 14

strengths
- inexpensive and easily accessed requiring minimal effort
- when examining secondary data, researcher may find that the desired info already exists so no need for conducting primary data collection
weaknesses
- variation in quality/accuracy as it may first appear valuable but on further investigation mat be outdated or incomplete
- data content may not match researcher’s objectives which may change validity of conclusions