Your project may include the following works (not limited to):
1. Find your own data from online resource. For example, you can find data from
UCI Machine Learning Repository. ([login to view URL])
2. Import the data into Matlab.
3. Give a brief explanation about your data, explain the columns you are interested
in. Show the first three rows of your data. If there are too many columns in your
data, just list the columns you are going to work on.
4. Clean and organize your data. For example
remove lines with missing values;
take a subset of data with columns you are interested in, or a subset by
rows depends on you analysis goal;
Note that if your cleaning work is done by other software (for example: excel),
that part of work won’t be counted for marks.
5. Try to understand the data by statistic measures. For example, you can choose
columns you are interested in, and measure the mean, variance, max, min, …
6. Try to understand the data pattern by plotting (i.e. 2-d plot, histogram, pie-
chart…), and explain your plot and you findings.
7. Add other computing columns to your data for easy analysis
8. Find the correlations between the columns you are interested, and explain your
9. Any other analysis you think helpful to understand and explain the data.
The grade will be determined by the following factors:
Writing: clear, brief and organized.
Analysis: sufficient, creative
Findings: good explanation based on your analysis results.