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
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.
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
Pushkar Dkcompleted 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)!
Deepal D'silvacompleted 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.