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Data Science Study Group: T-Tests & Z-Tests!

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Data Science Study Group: T-Tests & Z-Tests!

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Are you teaching yourself data science? Looking for a group of peers to bounce ideas off of or work on projects with? Curious about exploring data science as a career?

Then this group is for you!

Come join us at the Glen Park Library this Thursday, from 12:00 to 3:00, and hang out with other data science learners, collaborate, or work independently on your own course or project. We're an informal group, and all levels of experience are welcome.

This week we'll take a quick look at the theory behind t-tests and z-tests, and apply them to a real data set using Python. We'll look at street condition data in San Francisco from SF OpenData (https://data.sfgov.org/) to determine if the quality of streets in San Francisco increased, or decreased, in 2016.

NOTE: If you plan to follow along with the tutorial, please have jupyter notebooks installed before you arrive. Also have the following python modules installed: scipy, pandas, matplotlib, seaborn, numpy, and sklearn.

I recommend installing anaconda (https://www.continuum.io/downloads), which has python, jupyter notebooks, and all of the python modules that we'll be using installed with it.

If you would like to install the jupyter notebooks seperately, you can download it here (http://jupyter.org/). For downloading python modules seperately, you can use pip (https://pypi.python.org/pypi/pip). Modules we commonly use are: Pandas, Numpy, Matplotlib, Seaborn, Scikit-Learn, statsmodels.

I recommend this textbook (http://www-bcf.usc.edu/~gareth/ISL/) for learning the basics of statistical analysis (it's the text I referenced at the meetup).

Members are welcome to join in on the discussion or work on individual projects.

We’ve worked on the following so far:

This is a weekly, repeating "study group" event.

Anyone with an interest in Data Science is welcome.

Hope to see you there!

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