Udacity: Intro to Inferential Statistics

with  Katie Kormanik, Ronald Rogers and Sean Laraway
Inferential statistics allows us to draw conclusions from data that might not be immediately obvious. This course focuses on enhancing your ability to develop hypotheses and use common tests such as t-tests, ANOVA tests, and regression to validate your claims.

Why Take This Course?
This course will guide you through some of the basic tools of inferential statistics.

This course will cover:

- estimating parameters of a population using sample statistics
- hypothesis testing and confidence intervals
- t-tests and ANOVA
- correlation and regression
- chi-squared test

Syllabus

Inferential Statistics is a continuation of the material covered in [Descriptive Statistics](https://www.udacity.com/course/intro-to-descriptive-statistics--ud827), and so lesson numbers follow from that course:

### Lesson 8: Estimation
You will learn how to estimate population parameters from sample statistics using confidence intervals and estimating the effect of a treatment.
### Lesson 9: Hypothesis Testing
You will learn how to use critical values to make decisions on whether or not a treatment has changed the value of a population parameter.
### Lesson 10,11: t-tests
You will learn how to test the effect of a treatment or compare the difference in means for two groups when we have small sample sizes.
### Lesson 12,13: ANOVA
You will learn how to test whether or not there are differences between three or more groups.
### Lesson 14: Correlation
You will learn how to describe and test the strength of a relationship between two variables.
### Lesson 15: Regression
You will learn how to describe the way in which changes in one variable are related to changes in a second variable.
### Lesson 16: Chi-squared Tests
You will learn how to compare and test frequencies for categorical data.
### Final Project
You will use the methods you have learned in this course to perform an analysis on a dataset and report your findings. You will describe the data, calculate statistics, perform inference, and make conclusions.
8 Student
reviews
Cost Free Online Course
Pace Self Paced
Provider Udacity
Language English
Hours 6 hours a week
Calendar 8 weeks long

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Reviews for Udacity's Intro to Inferential Statistics 4.5 Based on 8 reviews

• 5 stars 63%
• 4 stars 25%
• 3 star 13%
• 2 star 0%
• 1 star 0%

Did you take this course? Share your experience with other students.

• 1
4.0 8 months ago
by completed this course, spending 7 hours a week on it and found the course difficulty to be medium.
A very good second course on elementary statistics. It requires us to finish 'descriptive statistics' before starting it and is a much lengthier course. However, the teaching style is very nice with emphasis on "why?" rather than simply calculating variables without understanding the concepts. The lecturers go to great lengths to help us visualize the data as well (I've come to believe that any course from Katie Kormanik must be easy to understand)!
5.0 a month ago
by completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
This is an excellent course for intermediate statistics. This course builds upon the Descriptive statistics course. The method of teaching focuses on understanding and applying various concepts rather than just plugging values in formulas.
5.0 a year ago
by is taking this course right now, spending 2 hours a week on it and found the course difficulty to be very easy.
Great course for getting started on Inferential Statistics. Very didactic. The teacher is great and all the concepts are very well explained
5.0 2 years ago
by completed this course, spending 15 hours a week on it and found the course difficulty to be medium.
1 person found
3.0 2 years ago
by completed this course.
0 person found
5.0 2 years ago
completed this course.
4.0 3 years ago
is taking this course right now.
1 person found