statistics for small datasets
There are four small datasets in this lab. You are to write a python package which contains a series of functions which can analyze these data sets. The package, statzcw, will have a series of python files, each of which implement a standard statistic.
- zcount(list: List[]) -> float
- zmean(list: List[]) -> float
- zmode(list: List[]) -> float
- zmedian(list: List[]) -> float
- zvariance(list: List[]) -> float
- zstddev(list: List[]) -> float
- zstderr(list: List[]) -> float
- zcorr(listx: List[], listy: List[]) -> float
You may only use the following functions to construct your code:
- python builtin
sum() - python builtin
max() - python builtin
min() - python Math function
Math.sqrt() - python normal operators on floats (*, /, +, -, etc)
The four data sets are each a list of two pairs of numbers (X and Y). Each of them are in a CSV file.
For each data set (0-3), print out the following statistical measures.
- Count of X
- Count of Y
- Mean of X
- Sample Variance of X
- Mean of Y
- SampleVariance of Y
- Correlation between X and Y (should be ~0.816)
Also produce the
- Median of X
- Median of Y
- Mode of X
- Mode of Y
- Sample Std deviation of X
- Sample Std Deviation of Y
- Standard Error of the Mean of X
- Standard Error of the Mean of Y
for all three datasets.
And then you are asked: "what do the statistics show you about these four data sets?"
Write a couple of unit tests to test your various functions within the package.
see Roughs.md for more info.