We all use a wide range of statistics in our everyday lives to make generalizations about the world or to make predictions about the future. An instruction to statistics course will teach you how statistics work and the essential terms you need to understand statistics. With a wide variety of intro to statistics online courses available, it’s easy for beginners to learn statistics.
Statisticians are one of the top 15 fastest-growing American jobs, so now is the time to start learning. The best statistics courses for beginners will give you a basic familiarity with a wide range of statistical methods and will teach you about the concept of correlation. In this article, we’ll cover the best introduction to statistics courses and other resources to learn statistics for beginners.
What Is Statistics?
Statistics is the science of using data sets to learn and make decisions. Statistics involves designing experimental data collection, choosing the right analysis method, visualizing data with bar graphs or scatter plots, and using the concept of correlation to make predictions about the larger population.
The future of statistics is bright since it is used by a wide range of industries. A common application is business statistics, used by business analysts, to assess a company’s performance and suggest areas for improvement. If you enjoy your intro to statistics, you might want to consider becoming a statistician.
How to Learn Statistics for Beginners
- Courses. Online and in-person courses are a fantastic way for beginners to learn statistics. An introduction to statistics course will give you all the basic knowledge you need.
- Websites. A wide variety of college majors require a course in statistics, so there are many university websites explaining statistical methods and statistical analysis.
- Books. How to Lie with Statistics by Darell Huff describes how political and business statistics can be used to mislead the average person. A textbook will have more detailed explanations and practice examples for practical applications of statistical concepts.
- YouTube videos. Many teachers upload videos on YouTube for students to learn and review different concepts. You can learn in detail about types of error, nonlinear models, probabilistic models, and sample statistics in short, digestible videos.
- Podcasts. You learn more about statistics in everyday life from podcasts. The Tufts University HiLab podcast has a number of episodes covering Bayesian models.
Best Statistics Courses for Beginners
| Course Name | Provider | Price | Duration |
|---|---|---|---|
| Basic Statistics | The University of Amsterdam and Coursera | $39 per month | 27 hours, self-paced |
| Basics of Statistical Inference and Modeling Using R | University of Canterbury and edX. | Free or $249 with verified certificate | 6 weeks, self-paced |
| Data Analysis and Fundamental Statistics | Future Learn | $39 per month | 4 weeks |
| Intro to Inferential Statistics | Udacity | Free | 2 months, self-paced |
| Intro to Statistics | Udacity | Free | 2 months, self-paced |
| Introduction to Probability and Data with R | Duke University and Coursera | $49 per month | 14 hours, self-paced |
| Introduction to Statistics | Stanford University and Coursera | Free or $79 with verified certificate | 15 hours, self-paced |
| Probability and Statistics for Business and Data Science | Udemy | $99.99 | 6 hours of lectures plus quizzes and exercises |
| Statistical Thinking for Data Science and Analytics | Columbia University and edX | Free or $99 for the verified track | 5 weeks, self-paced |
| Statistics for Data Science and Business Analysis | Udemy | $84.99 | 5 hours plus quizzes and exercises |
The Best Intro to Statistics Courses: Explained
Statistical analysis can be a challenging topic when you are just starting to learn. Below is a list of ten intro statistics courses for beginners. These courses will help you understand descriptive statistics, types of distributions, categorical variables, rules of probability, and more.
Basic Statistics | The University of Amsterdam and Coursera
In this course for beginners, students will learn about the relationship between dependent and independent variables, discrete distributions, probability distributions, and basic probability concepts. This course teaches students how to test hypotheses using R software.
Basics of Statistical Inference and Modeling Using R | University of Canterbury and edX
This intro course from University of Canterbury and edX teaches students statistical analysis through practical application. Topics covered include independent and dependent variables, categorical variables, bar graphs, sample statistics, and different analysis methods. Students who pay for the course will receive a professional certificate.
Data Analysis and Fundamental Statistics | Future Learn
This course from Future Learn is self-paced and entirely online. Students will learn about the fundamentals of statistics and how to apply them in statistical analysis. The learning outcome for this course includes using excel to analyze, clean, and manipulate data sets. After completion, you will receive a verified certificate.
Intro to Inferential Statistics | Udacity
After completing this online course you’ll be able to make predictions using statistical analysis. Key topics include estimation of population parameters, regression, correlation, and tests of significance. Students will learn to use three kinds of statistical tests, Chi-square Test, t-test, and hypothesis tests.
Intro to Statistics | Udacity
This introductory course provides students with knowledge about outliers, the normal distribution, confidence intervals, and linear models and includes an introduction to probability and bayesian probability. Students will learn to visualize data and use systematic techniques to understand the relationship between an independent and dependent variable.
Introduction to Probability and Data with R | Duke University and Coursera
This is the first course in the Statistics with R Specialization program offered by Duke University and Coursera. Students will learn to use R, a programming language used in statistical analysis, descriptive statistics, and data visualization. Students will learn about independent and dependent variables, descriptive statistics, and sampling methods.
Introduction to Statistics | Stanford University and Coursera
This online course is taught by Stanford University through Coursera. You will learn about statistical analysis through descriptive statistics, probability, the normal distribution, sampling distributions, categorical variables, and central limit theorem.
Probability and Statistics for Business and Data Science | Udemy
This online, self-paced course comes with 35 downloadable educational resources. The program covers the central limit theorem, conditional probability, the principles of sampling, and more. Once you complete the course, you will understand how to use statistical analysis to summarize data, perform statistical tests, and use statistical distributions to analyze business statistics.
Statistical Thinking for Data Science and Analytics | Columbia University and edX
This self-paced course will teach students about basic statistical analysis concepts, linear regressions, effective data visualization, and data-driven decision making. If you decide to pay for this course, you will receive a certificate and lifetime access to the learning materials.
Statistics for Data Science and Business Analysis | Udemy
Students will learn to use business statistics through videos, quizzes, and case studies. The curriculum covers essential topics such as regression analysis and probability distributions. After this program, you will be able to make data-driven decisions and calculate correlations.
Is Learning Statistics Worth It?
Yes, learning statistics is worth it because it is an essential part of many industries. Statistical methods are used to make data-driven decisions in our increasingly data-driven world. Learning about statistical methods will help you understand when different measurements are being used well or if they are being used to mislead you.
Introduction to Statistics FAQ
A normal distribution is a probability distribution used in statistical analysis to determine how likely an outcome is. It’s used in business statistics to determine if a new advertising campaign is impacting sales or if the change is just due to random chance.
According to the Bureau of Labor Statistics, the median salary for statisticians is $92,270. Statisticians work in a wide range of fields. Their responsibilities include presenting data with bar graphs, linear models, and charts, as well as using predictive methods to help different industries make data-driven decisions.
Yes, anyone can learn statistics. From popular books and articles to YouTube videos to online courses for beginners, there is a learning method out there for everyone.
Tests of significance are an analysis technique to see if there is a measurable difference between observed data and an expected result. Tests of significance use sample statistics and sampling distributions to make a conclusion.
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