1. Unseen Material

2. Qualitative Data
Thematic Analysis: – picking out themes and patterns in the data.

3. Thematic analysis
Thematic analysis involves generating codes, which can come from theory, from how the researcher understands their data or from previous research.
Steps:
Familiarise oneself with data
Generate codes
Look for themes in the codes
Review the themes
Define and name the themes
Produce a report

4. Thematic Analysis Strengths Maintains richness in data
Allows insights that are not anticipated by the researcher
Flexible way of analysing qualitative data – from theory or from data
Weaknesses
Subjectivity – researchers’ use their judgment to find themes.

5. The steps you followed in your practical
Step one: Read over your qualitative data. Step Two: Generate code. Label or a code is given to any specific categories Step three: Searching for themes from those codes. Do any themes come from the codes? Step four: Analysis you data and to find data to support your themes.

6. Example of Coding Data: Imagine you are doing qualitative research and are interested in analysing older adults online dating profiles in order to explore how older adults portray themselves to appear appealing to potential romantic partners.

7. Your Turn: Profile Two Profile Two Codes
I work part time and am involved in many activities. I am a dancer in a local dance club, a member of the dart club and enjoy lawn bowling in summer. Although I live alone, I have my family and friends nearby and enjoy socializing. I travel often, enjoy cruises and guided tours and being from England, and visit my family there. I have been on month long cruises through Asia, Hawaii, and Australia. I like to do Sudoku, crosswords, and watching the English soccer especially Liverpool so you can see I am a displaced scouse mind you I have posh scouse accent now  I would like to meet someone who I can go to a dance with and just talk to. If you have integrity and a sense of humour, send me an .

8. Let’s Compare

9. Developing Themes: The following codes have been identified from a piece of research on gender differences and prosocial behaviour
AIM: To investigate gender differences and prosocial behaviour on public transport.
Said thank you
Gave their seat up
Males
Made eye contact
Smiled at bus driver
Said, ‘thank you mate’
Shouted, thank you
Asked how are you?
Looked at phone while on bus
Looked at phone when they got off the bus
Whistled
Had headphones in
Had sunglasses on
Waved hand at women to get her attention
Said, Love do you want my seat?
Smiled
Moved bag from seat
Offered seat
Was listening to music
Read book
Looked ahead
Did not make eye contact
Female
Mumbled thank you
Waved at the bus driver
Smiled at Bus driver
Was drinking a bottle of water
Talking on phone
Talking to children
Chatting to a friend
Moved bag off seat but did say, ‘Do you want a seat?’
Avoided eye contact
Pretended to be sleeping and gave up seat reluctantly
Eating an apple

10. Question
Explain how you would analyse the qualitative data to investigate prosocial behaviour and gender. (4 marks)

11. Quantitative Data
Descriptive Mean Mode Median Measures of Disruption Rage Standard Deviation Inferential Chi Squared Spearman's rho

12. Question
According to Bandura (1961) boys are more physically aggressive than females. John wanted to conduct research to see if similar results would be found between gender and participation in aggressive sports. To establish what he meant by aggressive sport, John sampled 50, 17 year old teenagers (25 girls and 25 boys) and asked them to write down the name of two aggressive sports and two non-aggressive sports. He then narrowed the most aggressive sports to rugby. He narrowed the most non-aggressive sports to swimming. He sampled 100 Year 12 students at his school, through opportunity sampling, and during a games afternoon he gave each Year 12 student a choice of taking part in one of the two activities, he then observed how many of each gender took part in each sport. Here is the data that he collected:
Aggressive
Non Aggressive
Rugby
Swimming
Girls 20 41 24 15
Boys

13. State the IV: (1)
State the DV: (1)
3. Give a suitable one directional alternative hypothesis for this study. (2)
Explain one conclusion that can be drawn from the data in the table. (2)

14. Question 4 Marks Chi x ²: Observed Expected O-E (O-E)² (O-E)²/E Males
Rugby 41
34.16
Swimming 15
21.84
Females 20
26.84 24
17.16
4 Marks Chi x ²:

15. 3. Justify why you conducted a Chi x ² test. (2 marks) 4
3. Justify why you conducted a Chi x ² test. (2 marks) 4. Explain whether John’s data was significant and if the experimental hypothesis should be accepted. (2)

16. 4. Explain one weakness in using an opportunity sampling procedure, in Learning theories to investigate aggression. (2 marks)