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Statistical Decision Making in Data Science with Case Study

Understand how Statistics is Applied to Data Science Problem like ANOVA, t-test, F-test in Python
Free tutorial
Rating: 3.5 out of 5 (87 ratings)
18,354 students
52min of on-demand video
English
English [Auto]

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

Requirements

  • Understanding Statistics
  • Beginner to Python

Description

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 Statistics and 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 !!!

Who this course is for:

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

Instructors

Team of Engineers
Data Science Anywhere
  • 4.4 Instructor Rating
  • 1,984 Reviews
  • 85,049 Students
  • 18 Courses

Hi,

We're team of Machine Learning experts, AI developers working together to advance the state of the art in artificial intelligence. You will be hearing from us when new courses are released, answering Q&A and many more.

We are here to help you stay on the cutting edge of Data Science and Technology.


Thanks,

Data Science Anywhere Team

Data Scientist
Sudhir G
  • 3.9 Instructor Rating
  • 753 Reviews
  • 65,011 Students
  • 5 Courses

Sudhir is an experienced Data Scientist with a demonstrated history of working in the information technology and services industry. Skilled in Machine Learning, Deep Learning, Statistical algorithms he mostly worked on Image Processing and Natural Language processing application. He also successfully deployed many data science-related projects in cloud platforms as a service.  Strong engineering professional with a Bachelor's degree focused on Electrical and Electronics Engineering.

Convolution Innovations
  • 4.4 Instructor Rating
  • 1,937 Reviews
  • 83,118 Students
  • 16 Courses

Convolution Academy is a recently established educational institution that specializes in data science, machine learning, and web development. Founded by a team of experienced industry professionals, the academy is committed to providing high-quality education in these cutting-edge fields.

The academy offers a range of programs designed to equip students with the skills, knowledge, and practical experience they need to succeed in the rapidly evolving world of technology. Its instructors are experts in their respective fields and bring a wealth of industry experience to the classroom.

Convolution Academy's programs are designed to be hands-on and project-based, giving students the opportunity to work on real-world projects and build a portfolio of work that demonstrates their skills to potential employers. The academy also provides students with access to the latest tools and technologies in data science, machine learning, and web development, ensuring that they are well-prepared for the demands of the job market.

Convolution Academy is committed to creating an inclusive and supportive learning environment. Its programs are open to students of all backgrounds and levels of experience. The academy also provides students with resources and support beyond the classroom, including mentorship programs, career services, and community engagement initiatives.

The academy looks forward to continuing to innovate and push the boundaries of what is possible in these exciting fields


“Some lessons are learnt the hard way, but worth it.”

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