sonik8494 / inferential_stats_project

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Inferential Stats in Python

What have we learnt so far

In today's lecture we learned some probability concepts, learned about conditional probability and probability distributions.

We learned about the normal distribution and how using Central Limit theorem and properties of a Normal distribution we can do hypothesis testing, find confidence intervals for the population parameters.

We also learned about z-test and its limitations, t-test and chi-square tests of independence and GOF.

Why solve this assignment?

Lets review some of the concepts taught in the class. At the end of the assignment you'll be able to:

  • Understand conditional probability.
  • Build a confidence interval for a given sample mean, standard deviation and significance level.
  • Perform a one sample t-test to test to check if sample belongs to the population.
  • Check independence of two categorical variables.

Dataset

For this exercise, we will use the House Prices dataset, which we have already discussed in the session. You can read about the dataset description here.

By completing this project you have an opportunity to win 350 points

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Language:Python 71.7%Language:Jupyter Notebook 28.3%