Current Research - Undergraduate Supervision

This year, I'm fortunate enough to be supervising a number of interesting projects. A few of these can be completed entirely online. I'm sure my students would be grateful if you have a few spare minutes to take part. Finally, if you chose to leave your email address at the end, we can keep you notified of the results!

[CLOSED]
Perceptions towards everyday temporal experiences

Crime Anxiety

Where's the worst place to position a tattoo?

Attitudes towards video games

Exploring attitudes towards older adults

The Social Network

















Comments

Post a Comment

Popular posts from this blog

Apple Or Android? What Your Choice Of Operating System Says About You

Image
This post previously appeared on CREST's Blog in December 2016. Your mobile phone provides all kinds of useful data about what you do, and where. But does even the choice of handset say something about you? Heather Shaw and CREST Associate David Ellis tell us more. Digital traces can provide scientists and law-enforcement agencies with a range of information about groups and individuals. In particular, smartphones can log communications (e.g., calls and messages) and behaviour from multiple internal sensors (e.g., movement and location). For example, patterns of smartphone usage can be indicative of a person’s sleep-wake activity. Location information, on the other hand, is already used to provide alibis, and can accurately predict where a person works and lives. In a very short space of time, the smartphone has become a mini version of ourselves. This is probably why people become increasingly anxious if someone else attempts to use their smartphone! We found that A...
Read more

Kernel Density Plots: Has the histogram had its day?

Image
Simple statistical concepts include the mean, median, standard deviation, and percentiles. These are useful for summarising data. Except these summary statistics are only useful under certain circumstances. When basic assumptions are not met, then any conclusions based on simple summary statistics are likely to be inaccurate. Unable to give a hint as to what is wrong, the numbers can often look perfectly reasonable. Lets consider a sample of 64 reaction time observations (in milliseconds): Mean = 387ms Median = 340ms These look ok, until you view the distribution, which is not unimodal.  Despite being a staple in data visualisation, histograms can often be a poor method for determining the shape of a given distribution because they are strongly affected by the number of bins used. For example, visualising the same data with only four bins can make the same observations appear normally distributed. Similarly, a box-plot can also hide data irregulari...
Read more

Rosenberg self-esteem scale: SPSS Script

The Rosenberg self-esteem scale is a psychological inventory based on a 4-point likert scale and consists of 10 questions. It is used extensively to measure self-esteem across the social sciences. Below is a short script for SPSS which will help speed up the coding process.  All items should be labelled as separate numeric variables as R1, R2...etc The script computes and prints the results for all reverse-scored items and then calculates the total score.  *Part 1 - reverse scoring of specific items COMPUTE R3 = 5 - Q3. EXECUTE. COMPUTE R5 = 5 - Q5. EXECUTE. COMPUTE R8 = 5 - Q8. EXECUTE. COMPUTE R9 = 5 - Q9. EXECUTE. COMPUTE R10 = 5 - Q10. EXECUTE. *Part 2 - total score COMPUTE Rosenberg = Q1+Q2+R3+Q4+R5+Q6+Q7+R8+R9+R10. EXECUTE. *Reliability  RELIABILITY   /VARIABLES=Q1 Q2 R3 Q4 R5 Q6 Q7 R8 R9 R10   /SCALE('ALL VARIABLES') ALL   /MODEL=ALPHA.
Read more