There is no field of human endeavor where statistics is not required. That’s because every field involves the use of data.
Whether in academia, especially in research, banking, governance, industries, every kind of planning, the corporate world, and even sports, everything revolves around data.
You will have acquired excellent knowledge if you can successfully interpret and apply data.
Statistics courses help you not just personally but also provide skills in great demand globally. Learning Statistics online is an intelligent way of getting ahead. You also can learn at your own pace and from the comfort of your home.
Even if it seems Statistics is not a significant part of the industry you wish to work in, proficiency in data science is one of the most sought-after skills required today, so knowledge of it is a major career-improving step.
We have looked at some free courses and some paid ones. But all of them are guaranteed to add to your knowledge significantly.
But first, a brief overview of Statistics.
What is Statistics?
Statistics is the study of data collection, organization, and analysis, especially to infer proportions in a whole from those in a representative sample.
Although Statistics is a branch of mathematics, it is a discipline all by itself, which is why many universities have statistics departments.
Statistics could either be descriptive, that is, data is summarized through observations, or inferential, which is when statistics are used to interpret data.
Without much ado, let’s look at some of the best Statistics courses you can take online, how to take the course, how much it costs and what you stand to gain from them.
Some of the courses can be accessed free of charge, some are paid, and we have added a combination of courses.
Here we go.
#1 Statistics with R Specialisation by Coursera (Duke University)
About this course
Students who have enrolled for this class believe it is one of the best stats classes available online because of the features it offers.
Apart from having access to a certificate on completion, you can also include it in your CV or share it on your social profiles, especially on LinkedIn.
Statistics with R Specialisation allows you to create several data analysis projects, improve your ability to analyze statistical data, and apply for data science positions.
When through with this course, you will be able to learn how to visualize data in R and interpret, produce and analyze reports yourself.
Other concepts you will be able to grasp include understanding the unified nature of statistical inference, the ability to perform frequentist and Bayesian statistical inference, and communication of statistics-based results.
You will be able to understand statistical margins and visualize R packages for data analysis.
Also, you will learn how to perform hypothesis tests, interpret statistical results and report the results of your analysis to clients. You will be able to examine and utilize regression models to examine relationships between multiple variables.
More importantly, you’ll be able to install and use R and RStudio.
Although you have approximately five months to complete this course at a suggested rate of 2 hours per week, you can learn at your own pace. Also, you don’t need any prior experience to learn this course.
The course is presented in very interactive videos and is offered by Duke University.
How to apply
Once you have signed into your Coursera account, you can register for this course for free.
Cost
You can enroll in this course free of charge. However, you may have to pay to access the certificates.
Benefits
This course is very interactive. It also helps with hands-on projects, which earns you a certificate of completion. You also learn at your own pace and interact with instructors when you need to know more about anything.
#2 Statistical Thinking for Data Science and Analytics by EDX (Columbia University)
About this course
This Course is also foundational, so you don’t need any prior knowledge of statistics to learn it.
Also, this course will teach you how to understand statistical thinking and design collection of data and Its interpretation regardless of how complicated they seem.
You will also learn how to construct statistical models and use them to predict future trends from the data.
A summary of subjects covered includes data collection, data analysis, and data inference.
Others are data classification (to identify critical traits), conditional probability, using Bayesian modeling and inference for forecasting and studying public opinion, Using the Basics of Linear Regression, and using Data Visualization to create compelling graphics.
This self-paced course is estimated to take five weeks if you run it at about 5-7 hours per week. You can register free, although you can upgrade to a paid version.
This course is handled by professors at Columbia University and requires High School Math knowledge and some computer programming exposure.
How to apply
To apply for this program, enroll with edX, sign up for this course for audit course free, and upgrade to the paid version for access to more resources. To register, visit this page.
Cost
The paid version of this course costs $99 and provides access to unlimited materials and more. To audit the course, it’s free.
Benefits
With this course, you have unlimited access to course materials and education from a world-class university (Columbia).
You also have a certificate that you can use after completion of the course and have access to assignments and exams that would be graded.
#3 Statistics Courses (edX)
About this course
If you want to try other statistics courses with edX, here is where to apply. These courses are all designed to improve your learning of the subject.
We encourage you to check out this platform because it boasts some of the most popular statistics courses handled by professors at top universities. Since they are online, you can take them at your convenience and boost your career.
You can also choose the course you desire from a list of several courses and focus on the issues where you need knowledge the most. Topics covered include distributions, standard deviation, probability distributions, ANOVA, probability theory, and many more.
One does not need any prior knowledge of statistics to take most of these courses.
Examples of the courses you can take include Statistical Thinking for Data Science and Analytics, which we discussed earlier; Master the skills needed to solve complex data challenges; and Fundamentals of Statistics, both offered by the Massachusetts Institute of Technology; and Statistical Inference and Modeling for High-throughput Experiments, provided by Harvard University.
How to apply
Application for these courses is as simple as signing up with edX and selecting any of the courses under Statistics. You can apply here.
Cost
Most of the courses on the edX platform can be audited for free. But you can always upgrade to the paid version, where you access more resources and earn certificates on completion of assessments.
Benefits
If you pay for any of these courses, you can access unlimited materials. However, even with the free version, you can always get the best education from the best universities in the world.
#4 Intro to Statistics by Udacity (Stanford University)
About this course
This course deals with how to extract meaning from data. It is an introductory course that visualizes relationships in data and systematic techniques.
As an introductory course, topics you will learn include making predictions based on data, Simpson’s paradox, Probability, Bayes Rule, Correlation vs. Causation, and more.
You are also exposed to maximum likelihood estimation, Mean, Median, Mode, Standard Deviation and Variance, and other advanced concepts like Outliers, Binomial Distribution, Linear regression, Correlation, and Hypothesis Testing.
Stanford University teaches the course, and you earn a certificate on completion. It is a self-paced course that runs for eight weeks and is available on Udacity for free.
How to apply
The course is available for registration on Udacity, and you can register here.
Cost
You can register for Intro to Statistics for free via Udacity.
Benefits
This course is taught free and can be learned at your pace. It is very interactive and provides certificates on completion.
#5 Statistics / Data Analysis in SPSS: Inferential Statistics by Udemy
About this course
With this course, you will be able to learn how to use SPSS to analyze data and inferential statistics to draw accurate conclusions about a large population.
You’ll also be able to determine the appropriate statistical test required for each data set. The course is easy to understand and has lots of illustrations that can help you better understand.
Also, the course allows you to master how to write your statistical analysis results in APA format, which is the most appropriate format for writing statistical analysis results.
The course is divided into different segments. They touch on topic