NSCS 344, Week 7:

Assignment 7: Handling data in Matlab

Part 1: Look at the data (2 points)

• Download the behavioral data from D2L
• Note: if you are doing the course online and are NOT at the University of Arizona, you can download a "fake" dataset here
• Load it into Matlab
• Use "whos" to see what variables have been loaded
• Print out the text of the questions to the Command Line
• Follow along with the notes to image the choice data

Part 2: Plot the choice curves of people (2 points)

• Follow along with the notes to plot the average choice curve of all participants in the data set
• Make sure you have EV_safe - EV_risky on the x-axis and f_safe on the y-axis
• Plot three choice curves for three individual people from the data set. Note the choice probabilities here will be either 0 or 1 because each person only makes one choice for each.

Part 3: Plot the softmax choice curve with the human choice curve

• Follow along with the notes to plot the softmax choice curve on the same plot as the human choice curve.
• Start with a value of sigma = 3
• Then make the same plot but with a smaller sigma (e.g. sigma = 1) and then a larger sigma (e.g. sigma = 10)
• Finally, see if you can tweak sigma to get as close as you can to the human curve. What's your best guess for sigma? What does that mean?

Part 4: Process the blink rates (2 points)

• Follow along with the text to compute the mean blink rate
• Use the nanmedian function to compute the median blink rate
• Use the nanstd function to compute the standard deviation of the blink rate
• Use the max and min functions to compute the max and minimum blink rates in the data set
• Plot the histogram of blink rates using the hist function

Part 5: Individual differences in risk taking (2 points)

• Follow along with the notes to compute the average risk taking for each person
• Use the hist function to compute the distribution over the average number of times people choose the risky option

Part 6: The correlation between risk taking and blink rate (2 extra credit points)

• Plot the relationship between risk taking and blink rate
• Use the lsline function to add a best fitting straight line
• Use the corr function to determine whether there is a statistically significant relationship between blink rate and risk taking.

Part 7: Looking at the relationship between blinks and choice in a different way (2 more extra credit points!)