Topic: A paradox of choice–do people maximise or satisfy and why? (title)

Order Description
A research report on maximising and satisficing (study B in additional files), the topic provided is made up by myself, you can change to another title if you wish.
Focal measure of the study, and the individual difference(s) that it examines: The Schwartz et al. Maximizing Scale.
1.5 line spacing.
Basic guideline and structure: (see attachment files for more details)
Abstract (max 150 words)
Introduction (~550 words)
• Background literature
• Links to previous research (findings from previous research, how you got those)
• Rationale
• Aims/hypothesis
• ‘Gap’ in the literature
• Predict purpose
• Why its important
Method
• Participants criteria for exclusion and inclusion sampling method
• Design of study
• Operationalising variables
• Equipment and materials
• Procedure diagrams if relevant (be brief)
• Conditions
Results
• Statistical analysis
– Descriptive
– Inferential
• State results
• State tests used and significance levels
• Supporting diagrams and images
• Conclusion and findings
– What does it mean?
Discussion
• Restate hypothesis
• Conclusions—outline main findings
• Implication to to other research and theories
• Limitations and strengths
– Validity
– Reliability
• Implications of meaning
– Real world application
• Generalizability
• Future research opportunities (ideas for future studies)
• Ethical consideration
References
Appendix
Data analysis (choose about 2 or more from below to analyse in deep details):
1. Examine the internal consistency of the maximizing and regret scales.
• Cronbach’s alpha to measure internal consistency of a measure.
• Use SPSS to identity items that do not fit well with other items from the same scale.

2. Examine whether maximising scores are related to regret scores or operation span.
(examining divergent validity, and possible sources of variation in maximizing)
• People satisfy as they find it difficult to maximize due to cognitive capacity. So operation span can be related to scores on the maximizing scale.
• Tendency to experience regret might also lead people to put a lot of effort into choosing. Therefore, could examine whether maximizing scores are related to regret scores or operation span.
• If maximizing was very strongly related to regret could imply that they are not distinct constructs. Hence, we might be concerned.
• So if regret and maximizing scores are strongly correlated, we could explore whether it would be better to have a single scale that had items from both scales than to have two separate scales.

3. Test whether maximizing scores predict the amount of information collected in the data sampling tasks. (examining predictive validity)
• Analyse the relationship between maximizing scores and the amount of information collected in the two decision-from-samples tasks (using correlation or regression).
[As we know ‘maximizers’ need to examine all the details of their options in case there is a better option than their current favourite, while ‘satisficers’ can stop looking at information as soon as they find an option that satisfies their requirements.]
• There were considerable individual differences in the amount of information collected in these tasks, so you may have to be alert to the influence of outliers in these analyses.
• Examine the consistency of information collection behaviour across the different elements of the decision-from-samples tasks (e.g., do those who collect more information in one task also collect more in another task).

4. Test whether maximizing scores predict the amount of information collected in the data sampling tasks. (examining predictive validity)
• Previous research has found that working memory capacity is positively correlated with the amount of information collected in decision-from-samples tasks (Rakow, Demes & Newell, 2008). (This can be examined in our data)
• We can also examine whether the regret scores predict the amount of information collected in decision-from-samples tasks.
• The strength of these relationships can be compared with those for analysis 3. above.

5. Examine whether maximising scores predict information collection better than regret scores of operation span scores; and whether maximizing scores still predict information collection when controlling for regret or for operation span.
• If regret scores and operation span scores are related to maximizing scores, then you can examine whether these explain some or all of the relationship between maximizing and the amount of information collected in decision-from-samples tasks.
• This could be done by finding the partial correlation between maximizing scores and the amount of information collected in a decision-from- samples task while controlling for regret (or operation span).

Key points for the report:
1. Use headings and subheadings.
2. Introduction and discussion should mirror each other
3. Introduction starts with research related to your topic and then narrow your approach, clearly state research question and hypothesis and ensure you answer them in the discussion.
4. Put the present study into perspective of past research and discuss implications of findings for future research.
5. Asking questions, asking leading sentences and phrases to make it flow better
6. Use of supporting research
7. Use of subtitles and clear subsections
3. Use headings or sub-headings

For more information and data please see attachment files.

Topic: A paradox of choice–do people maximise or satisfy and why? (title)

Order Description
A research report on maximising and satisficing (study B in additional files), the topic provided is made up by myself, you can change to another title if you wish.
Focal measure of the study, and the individual difference(s) that it examines: The Schwartz et al. Maximizing Scale.
1.5 line spacing.
Basic guideline and structure: (see attachment files for more details)
Abstract (max 150 words)
Introduction (~550 words)
• Background literature
• Links to previous research (findings from previous research, how you got those)
• Rationale
• Aims/hypothesis
• ‘Gap’ in the literature
• Predict purpose
• Why its important
Method
• Participants criteria for exclusion and inclusion sampling method
• Design of study
• Operationalising variables
• Equipment and materials
• Procedure diagrams if relevant (be brief)
• Conditions
Results
• Statistical analysis
– Descriptive
– Inferential
• State results
• State tests used and significance levels
• Supporting diagrams and images
• Conclusion and findings
– What does it mean?
Discussion
• Restate hypothesis
• Conclusions—outline main findings
• Implication to to other research and theories
• Limitations and strengths
– Validity
– Reliability
• Implications of meaning
– Real world application
• Generalizability
• Future research opportunities (ideas for future studies)
• Ethical consideration
References
Appendix
Data analysis (choose about 2 or more from below to analyse in deep details):
1. Examine the internal consistency of the maximizing and regret scales.
• Cronbach’s alpha to measure internal consistency of a measure.
• Use SPSS to identity items that do not fit well with other items from the same scale.

2. Examine whether maximising scores are related to regret scores or operation span.
(examining divergent validity, and possible sources of variation in maximizing)
• People satisfy as they find it difficult to maximize due to cognitive capacity. So operation span can be related to scores on the maximizing scale.
• Tendency to experience regret might also lead people to put a lot of effort into choosing. Therefore, could examine whether maximizing scores are related to regret scores or operation span.
• If maximizing was very strongly related to regret could imply that they are not distinct constructs. Hence, we might be concerned.
• So if regret and maximizing scores are strongly correlated, we could explore whether it would be better to have a single scale that had items from both scales than to have two separate scales.

3. Test whether maximizing scores predict the amount of information collected in the data sampling tasks. (examining predictive validity)
• Analyse the relationship between maximizing scores and the amount of information collected in the two decision-from-samples tasks (using correlation or regression).
[As we know ‘maximizers’ need to examine all the details of their options in case there is a better option than their current favourite, while ‘satisficers’ can stop looking at information as soon as they find an option that satisfies their requirements.]
• There were considerable individual differences in the amount of information collected in these tasks, so you may have to be alert to the influence of outliers in these analyses.
• Examine the consistency of information collection behaviour across the different elements of the decision-from-samples tasks (e.g., do those who collect more information in one task also collect more in another task).

4. Test whether maximizing scores predict the amount of information collected in the data sampling tasks. (examining predictive validity)
• Previous research has found that working memory capacity is positively correlated with the amount of information collected in decision-from-samples tasks (Rakow, Demes & Newell, 2008). (This can be examined in our data)
• We can also examine whether the regret scores predict the amount of information collected in decision-from-samples tasks.
• The strength of these relationships can be compared with those for analysis 3. above.

5. Examine whether maximising scores predict information collection better than regret scores of operation span scores; and whether maximizing scores still predict information collection when controlling for regret or for operation span.
• If regret scores and operation span scores are related to maximizing scores, then you can examine whether these explain some or all of the relationship between maximizing and the amount of information collected in decision-from-samples tasks.
• This could be done by finding the partial correlation between maximizing scores and the amount of information collected in a decision-from- samples task while controlling for regret (or operation span).

Key points for the report:
1. Use headings and subheadings.
2. Introduction and discussion should mirror each other
3. Introduction starts with research related to your topic and then narrow your approach, clearly state research question and hypothesis and ensure you answer them in the discussion.
4. Put the present study into perspective of past research and discuss implications of findings for future research.
5. Asking questions, asking leading sentences and phrases to make it flow better
6. Use of supporting research
7. Use of subtitles and clear subsections
3. Use headings or sub-headings

For more information and data please see attachment files.