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Statistical Decision Making in Data Science with Case Study

  • Development
  • Mar 16, 2025
SynopsisStatistical Decision Making in Data Science with Case Study,...
Statistical Decision Making in Data Science with Case Study  No.1

Statistical Decision Making in Data Science with Case Study, available at Free, has an average rating of 4.55, with 14 lectures, based on 98 reviews, and has 19247 subscribers.

You will learn about Least Square Regression Build OLS in Statsmodel Hypothesis Testing t test ANOVA F Statistics Degree of Freedom of the Model Plotting Regression Line above the scatter plot (Fitted Values) Predicting Results Answer Question statistically This course is ideal for individuals who are Beginner of Python Developer who want to learn Data Science or Solving question related to linear regression It is particularly useful for Beginner of Python Developer who want to learn Data Science or Solving question related to linear regression.

Enroll now: Statistical Decision Making in Data Science with Case Study

Summary

Title: Statistical Decision Making in Data Science with Case Study

Price: Free

Average Rating: 4.55

Number of Lectures: 14

Number of Published Lectures: 14

Number of Curriculum Items: 14

Number of Published Curriculum Objects: 14

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

  • Least Square Regression
  • Build OLS in Statsmodel
  • Hypothesis Testing
  • t test
  • ANOVA
  • F Statistics
  • Degree of Freedom of the Model
  • Plotting Regression Line above the scatter plot (Fitted Values)
  • Predicting Results
  • Answer Question statistically
  • Who Should Attend

  • Beginner of Python Developer who want to learn Data Science
  • Solving question related to linear regression
  • Target Audiences

  • Beginner of Python Developer who want to learn Data Science
  • Solving question related to linear regression
  • Welcome to the course “Statistical Decision Making in Data Science with a Case Study in Python”

    This course is an introduction course where you will learn about the importance of Statisticsand Machine Learning in Decision Making. I explained this course with a case study. We start with a problem statement and data then we build the machine learning model. Building a machine learning model is really not enough but getting a decision out of machine learning is the primary goal in Data Science. For that, we will use statistics.

    What you will Learn?

    1. Understand the Problem statement (Case Study on Big Mac Index with used in Forex Industry for Predicting Dollar value)

    2. Asking Statistical Question.

    3. Linear Regression (Least Square Regression)

    4. Develop Least Square Regression in Python.

    5. Understand the Outputs

      1. MSE

      2. Degree of Freedom

    6. Hypothesis testing

      1. t-test for coefficient significance

      2. F-test for model significance

      3. ANOVA

    7. Correlation

    8. R-Square

    You will learn the approaches towards regression with case study.  First we start with understanding linear equation and the optimization function value sum of squared errors.  With that we find the values of the coefficient and makes least square regression. Then we starts building our linear regression in python.

    For the model we build we necessary test like hypothesis testing.

  • t-test for coefficient significance

  • ANOVA and F-test for model significance.

  • And finally, we answer the question statically. Hope we are seeing you inside the course !!!

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: Google Colab

    Chapter 2: Case Study – Big Mac Index

    Lecture 1: Big Mac Index Case Study Walk through

    Chapter 3: Least Square Regression

    Lecture 1: Least Square RegressionLinear Regression , y = a+b X and SSE

    Chapter 4: Least Square Regression in Python

    Lecture 1: Load Data & Scatter Plot

    Lecture 2: Fitting Ordinary Least Square Regression Model in Python

    Chapter 5: Hypothesis Testing to model

    Lecture 1: Degree of Freedom of the Model

    Lecture 2: Hypothesis testing : t – test

    Lecture 3: Fitted Values

    Lecture 4: Hypothesis testing : ANOVA

    Lecture 5: F – Statistics in Python

    Lecture 6: R Square

    Lecture 7: Answers

    Chapter 6: Bonus

    Lecture 1: bonus

    Instructors

  • Statistical Decision Making in Data Science with Case Study  No.2
    datascience Anywhere
    Team of Engineers
  • Statistical Decision Making in Data Science with Case Study  No.3
    Sudhir G
    Data Scientist
  • Statistical Decision Making in Data Science with Case Study  No.4
    Convolution Innovations
    Academy
  • Rating Distribution

  • 1 stars: 4 votes
  • 2 stars: 7 votes
  • 3 stars: 11 votes
  • 4 stars: 31 votes
  • 5 stars: 45 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

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