Foundations of Data Analysis - Part 2: Inferential Statistics

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10/10 stars
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Foundations of Data Analysis - Part 2: Inferential Statistics

Course Details

Cost

FREE

Upcoming Schedule

  • On demand

Course Provider

edX online courses
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be tau...
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

Provider Subject Specialization
Sciences & Technology
Business & Management
22212 reviews

Course Description

In the second part of a two part statistics course, we’ll learn how to take data and use it to make reasonable and useful conclusions. You’ll learn the basics of statistical thinking – starting with an interesting question and some data. Then, we’ll apply the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

We will cover basic Inferential Statistics – integrating ideas of Part 1. If you have a basic knowledge of Descriptive Statistics, this course is for you. We will learn how to sample data, examine both quantitative and categorical data with statistical techniques such as t-tests, chi-square, ANOVA, and Regression.

Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intent...

In the second part of a two part statistics course, we’ll learn how to take data and use it to make reasonable and useful conclusions. You’ll learn the basics of statistical thinking – starting with an interesting question and some data. Then, we’ll apply the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

We will cover basic Inferential Statistics – integrating ideas of Part 1. If you have a basic knowledge of Descriptive Statistics, this course is for you. We will learn how to sample data, examine both quantitative and categorical data with statistical techniques such as t-tests, chi-square, ANOVA, and Regression.

Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R).

This course will consist of:

  • Instructional videos for statistical concepts broken down into manageable topics
  • Guided questions to help your understanding of the topic
  • Weekly tutorial videos for using R
  • Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets
  • Weekly wrap-up questions challenging both topic and application knowledge

With these new skills, learners will leave the course with the ability to use basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R). Learners from all walks of life can use this course to better understand their data, to make valuable informed decisions.

Join us in learning how to look at the world around us. What are the questions? How can we answer them? And what do those answers tell us about the world we live in?

Reviews 10/10 stars
5 Reviews for Foundations of Data Analysis - Part 2: Inferential Statistics

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Yaroslav Verkh profile image
Yaroslav Verkh profile image

Yaroslav Verkh

10/10 starsCompleted
2 years, 4 months ago
Great course on statistics. It explains both the basics and the more complex concepts so that one gets a good explanation for why certain thing are being done or where they are coming from. The instructor did a fantastic job explaining the contents in an entertaining, simple and understandable way.
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student

10/10 starsCompleted
3 years, 1 month ago
It follows the same pattern and structure as Part 1. Part 2 focuses on Hypothesis Testing, and it introduces different techniques in a clear and firendly way. R is used as a tool,learning how to use it is not the focus of the course.Material is very well organized, content is clear and focus on main ideas. Exercises help to understand key concepts. I totally recommend it, and also Part 1.
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Jorge Jasso profile image
Jorge Jasso profile image

Jorge Jasso

10/10 starsCompleted
3 years, 1 month ago
Excellent course! I took part 1 and enjoyed it a lot, so it was very easy to decide to go on with part 2. Dr. Mahometa and team are very good teachers and their material is of a very high quality. The exercises are interesting and the materials (videos, labs and problems) are appropriate and well chosen. I recommend this course to any one interested in statistical analysis (as an introduction to machine learning, big data, data science, etc.). The topics for part 2 are: Sampling, Hypothesis Testing (One Group Means), Hypothesis Testing (Two Group Means), Hypothesis Testing (Categorical Data), Hypothesis Testing (More Than Two Group Means), and Correlation and Regression. In a scale from 1 to 10 I give 50!
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Sumeet Malik profile image
Sumeet Malik profile image

Sumeet Malik

10/10 starsTaking Now
3 years, 2 months ago
Excellent course! I took Prof. Mahometa's part 1 of the course and fell in love with R(with no prior knowledge). This I think can be taken individually but might have a steeper learning curve. The course is designed beautifully with pre-labs, labs and assignments that cement the concepts learned through text and videos. I have been around on Edx since it started and I must say it is hard to find such well designed course and that too for free. I hope Prof. Mahometa design more courses on advanced topics. It will be a treat to learn.
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Bernard Osei Afriyie profile image
Bernard Osei Afriyie profile image

Bernard Osei Afriyie

10/10 starsTaking Now
3 years, 2 months ago
i think it is about inferential statistics.it will broaden my knowledge on making a good hypothesis and make good judgements,.
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