IBM
Statistics for Data Science with Python
IBM

Statistics for Data Science with Python

Murtaza Haider
Aije Egwaikhide

Instructors: Murtaza Haider

33,905 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.5

(393 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

(393 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

12 quizzes

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.
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  • 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 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
4.4 (146 ratings)
Murtaza Haider
IBM
3 Courses39,168 learners
Aije Egwaikhide
IBM
6 Courses636,748 learners

Offered by

IBM

Recommended if you're interested in Probability and Statistics

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4.5

393 reviews

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AS
5

Reviewed on May 2, 2022

OA
4

Reviewed on Apr 4, 2021

PK
5

Reviewed on May 29, 2022

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