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.