IBM
Statistics for Data Science with Python
IBM

Statistics for Data Science with Python

This course is part of Data Science Fundamentals with Python and SQL Specialization

Taught in English

Some content may not be translated

Murtaza Haider
Aije Egwaikhide

Instructors: Murtaza Haider

29,705 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.5

(364 reviews)

|

91%

14 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Write Python code to conduct various statistical tests including a T test, an ANOVA, and regression analysis.

  • Interpret the results of your statistical analysis after conducting hypothesis testing.

  • Calculate descriptive statistics and visualization by writing Python code.

  • Create a final project that demonstrates your understanding of various statistical test using Python and evaluate your peer's projects.

Details to know

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.5

(364 reviews)

|

91%

14 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Data Science Fundamentals with Python and SQL Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 9 modules in this course

Welcome!

What's included

2 videos2 readings1 app item

This module will focus on introducing the basics of descriptive statistics - mean, median, mode, variance, and standard deviation. It will explain the usefulness of the measures of central tendency and dispersion for different levels of measurement.

What's included

4 videos2 quizzes1 app item

This module will focus on different types of visualization depending on the type of data and information we are trying to communicate. You will learn to calculate and interpret these measures and graphs.

What's included

4 videos2 quizzes1 app item

This module will introduce the basic concepts and application of probability and probability distributions.

What's included

5 videos2 readings2 quizzes1 app item

This module will focus on teaching the appropriate test to use when dealing with data and relationships between them. It will explain the assumptions of each test and the appropriate language when interpreting the results of a hypothesis test.

What's included

5 videos2 quizzes1 app item

This module will dive straight into using python to run regression analysis for testing relationships and differences in sample and population means rather than the classical hypothesis testing and how to interpret them.

What's included

4 videos2 quizzes1 app item

In the final week of the course, you will be given a dataset and a scenario where you will use descriptive statistics and hypothesis testing to give some insights about the data you were provided. You will use Watson studio for your analysis and upload your notebook for a peer review and will also review a peer's project. The readings in this module contain the complete information you need.

What's included

8 readings1 peer review2 app items

What's included

1 quiz

Cheat sheet for Statistics in Python

What's included

1 reading1 quiz1 plugin

Instructors

Instructor ratings
4.3 (137 ratings)
Murtaza Haider
IBM
3 Courses31,932 learners
Aije Egwaikhide
IBM
6 Courses570,488 learners

Offered by

IBM

Recommended if you're interested in Probability and Statistics

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4.5

364 reviews

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PK
5

Reviewed on May 29, 2022

OA
4

Reviewed on Apr 4, 2021

HD
5

Reviewed on Jan 13, 2021

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