Statistics (Udacity)

Statistics (Udacity)

The Science of Decisions. We live in a time of unprecedented access to information...data. Whether researching the best school, job, or relationship, the Internet has thrown open the doors to vast pools of data. Statistics are simply objective and systematic methods for describing and interpreting information so that you may make the most informed decisions about life.

Class Deals by MOOC List - Click here and see Udacity's Active Discounts, Deals, and Promo Codes.

NOTE: This course has been divided into two courses: Descriptive and Inferential Statistics. If you are new to statistics, we recommend taking these courses instead.

What You Will Learn

Lesson 1
Introduction to Statistics and Methods

  • Intro to statistical research methods
  • Frequency Distributions & Visualizing data

Lesson 2
Describing Data

  • Central Tendency
  • Variability

Lesson 3
Normal Distribution Analysis

  • Standardized Scores (z-scores)
  • Probability and the Normal Distribution
  • Sampling Distributions

Lesson 4
Foundations of Inferential Statistics

  • Estimation
  • Hypothesis Testing

Lesson 5
Comparing Means

  • t-tests
  • One-way ANOVA

Lesson 6
Correlation, Regression, and Non-Parametrics

  • Correlation
  • Regression
  • Chi-Squared Tests

Prerequisites and Requirements
It sounds strange to say, but math is not the focus of this class. To do well, however, it is necessary to have a basic understanding of proportions (fractions, decimals, and percentages), negative numbers, basic algebra (solving equations), and exponents and square roots.

Why Take This Course

  • The applications of statistics to everyday life
  • Methods for acquiring data through observation and experimentation
  • To organize and describe quantitative and categorical forms of data
  • Anticipating patterns using basic probability and sampling
  • Statistical inference through estimation and hypothesis testing
  • Correlation and simple regression
  • Ways of describing the strength of relationships between variables
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Statistics and Data Analysis with Excel, Part 2 (Coursera) Coursera
University of Colorado Boulder

Statistics and Data Analysis with Excel, Part 2 (Coursera)

This course is meant to be a direct continuation of "Statistics and Data Analysis with Excel, Part 1." Therefore, it is not recommended to take Part 2 unless you've also taken Part 1. Building on the topics learned in Part 1 of the course (probability, probability mass and density functions, the normal and standard normal distributions), this course dives into a more applied side of statistics.

Nov 16th 2026
5-12 Weeks
Causal Inference (Coursera) Coursera
Columbia University

Causal Inference (Coursera)

This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships.

Nov 16th 2026
5-12 Weeks
Mathematical Biostatistics Boot Camp 1 (Coursera) Coursera
Johns Hopkins University

Mathematical Biostatistics Boot Camp 1 (Coursera)

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

Nov 9th 2026
4 Weeks
Data Analysis with R (Udacity) Udacity
Udacity,Facebook

Data Analysis with R (Udacity)

Visually Analyze and Summarize Data Sets. Exploratory data analysis is an approach for summarizing and visualizing the important characteristics of a data set. Promoted by John Tukey, exploratory data analysis focuses on exploring data to understand the data’s underlying structure and variables, to develop intuition about the data set, to consider how that data set came into existence, and to decide how it can be investigated with more formal statistical methods.

Self Paced
Self-Paced
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Nov 16th 2026
5-12 Weeks
Studying Cities: Social Science Methods for Urban Research (Coursera) Coursera
Erasmus University Rotterdam

Studying Cities: Social Science Methods for Urban Research (Coursera)

Are you looking to learn more about how to conduct scientific research, specifically in an urban or local context? Then you have found the right course: Studying Cities: Social Science Methods for Urban Research by the Institute for Housing and Urban Development Studies (IHS), Erasmus University Rotterdam. During the course you will gain more insight in the different steps of the research cycle, and build a firm foundation for your own future research endeavors.

Nov 9th 2026
5-12 Weeks