IBM
Statistics for Data Science with Python
IBM

Statistics for Data Science with Python

Murtaza Haider
Aije Egwaikhide

Instructors: Murtaza Haider

34,521 already enrolled

Included withCoursera Plus

Gain insight into a topic and learn the fundamentals.
4.5

(403 reviews)

14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
91%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.5

(403 reviews)

14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
91%
Most learners liked this course

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

6 quizzes, 6 assignments

Taught in English

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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
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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 assignments1 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 assignments1 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 assignment

Cheat sheet for Statistics in Python

What's included

1 reading1 assignment1 plugin

Instructors

Instructor ratings
4.4 (150 ratings)
Murtaza Haider
IBM
3 Courses40,196 learners
Aije Egwaikhide
IBM
6 Courses644,668 learners

Offered by

IBM

Recommended if you're interested in Probability and Statistics

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4.5

403 reviews

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RD
5

Reviewed on Aug 25, 2024

OA
4

Reviewed on Apr 4, 2021

MI
4

Reviewed on Mar 9, 2023

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