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Statistical Decision Making in Data Science with Case Study

Description

Welcome to the course “Statistical Decision Making in Data Science with a Case Study in Python”

This course is an introduction course the place you’ll be taught in regards to the significance of Statistics and Machine Studying in Decision Making. I defined this course with a case research. We begin with an issue assertion and information then we construct the machine studying mannequin. Constructing a machine studying mannequin is basically not sufficient however getting a choice out of machine studying is the first purpose in Data Science. For that, we are going to use statistics.

What you’ll Be taught?

  1. Perceive the Downside assertion (Case Study on Massive Mac Index with used in Foreign exchange Trade for Predicting Greenback worth)

  2. Asking Statistical Query.

  3. Linear Regression (Least Sq. Regression)

  4. Develop Least Sq. Regression in Python.

  5. Perceive the Outputs

    1. MSE

    2. Diploma of Freedom

  6. Speculation testing

    1. t-test for coefficient significance

    2. F-test for mannequin significance

    3. ANOVA

  7. Correlation

  8. R-Sq.

You’ll be taught the approaches in direction of regression with case research.  First we begin with understanding linear equation and the optimization operate worth sum of squared errors.  With that we discover the values of the coefficient and makes least sq. regression. Then we begins constructing our linear regression in python.

For the mannequin we construct we essential check like speculation testing.

  • t-test for coefficient significance

  • ANOVA and F-test for mannequin significance.

And at last, we reply the query statically. Hope we’re seeing you contained in the course !!!


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