Udacity

Intro to Inferential Statistics (Udacity)

Offered by Udacity,

Making Predictions from Data. 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.

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What You Will Learn

Lesson 1
Estimation

Estimate population parameters from sample statistics using confidence intervals.
Estimate the effect of a treatment.

Lesson 2
Hypothesis Testing

How to determine if a treatment has changed the value of a population parameter.

Lesson 3
t-tests

How to test the effect of a treatment.
Compare the difference in means for two groups when there are small sample sizes.

Lesson 4
ANOVA

Learn how to test whether or not there are differences between three or more groups.

Lesson 5
Correlation

Learn how to describe and test the strength of a relationship between two variables.

Lesson 6
Regression

How changes in one variable are related to changes in a second variable.

Lesson 7
Chi-squared Tests

Learn how to compare and test frequencies for categorical data.

Prerequisites and Requirements
This course assumes basic understanding of Descriptive Statistics, specifically the following:

calculating the mean and standard deviation of a data set
central limit theorem
interpreting probability and probability distributions
normal distributions and sampling distributions
normalizing observations

If you need a refresher, check out our [Descriptive Statistics course!]() The course also utilizes Google Spreadsheets as a tool.

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

Go to Class

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