Is learning statistics important for data science?
Statistics is an essential pillar of studying data science across all its niches.
While it’s true that there are many tools available today that have reduced the computation work for us, to truly understand the math and principles that drive data and our work, it’s essential to have a good understanding of statistics.
Otherwise, we’d just be good tool experts, as opposed to being great data analysts. What’s more, before we even feed raw data to any software, the right statistical knowledge enables us to source and clean data so that we get quality results.
It’s clear how vital it is to learn statistics, and these statistics courses are an excellent place to start.
In this guide, I’ll be taking you through the best statistics courses online for data science in 2023 that will help set your career in motion.
Let’s get started.
1. Statistics for Data Science and Business Analysis [Udemy]
Would you like to make data-driven business decisions?
Then this training can help with business intelligence in the following ways:
- Via regression analysis, which helps establish data point relationships, you can better understand supply and demand. This is therefore one of the best statistics courses on Udemy for predicting sales.
- By addressing both descriptive and inferential statistics, you get to understand data as it exists for better presentation and also how it is bound to change and influence future strategies.
- With examples that reflect real-life business scenarios, this course provides practical concepts for you to straight away adopt to improve business processes.
However, there are fewer practice exercises towards the end. Overall though, there are plenty of data sets to work with so it remains the best statistics course online for business analysis and data science as well.
2. Introduction to Statistics [Coursera]
For an entry-level introduction to statistics, this tutorial will get you started with exploratory data analysis and other important topics.
You’ll get to learn about:
- The common pitfalls that you’ll encounter when sampling data during experiments. As a result, this is one of the best statistics courses on Coursera for designing effective data experiments.
- Regression diagnostics to help determine if there is a good representation of sample data in a particular model.
- The Normal Approximation to the Binomial Distribution, which will be of help in approximating the probabilities of random variables in a large range.
Course support in the discussion forum may be hard to come by because of instructor unavailability. Nonetheless, the student community is quite active and you can get any help you may need from there. It’s unlikely though that you’ll need it because the course is well put-together.
3. Statistics Foundations: The Basics [LinkedIn Learning]
For a crash course on the basics of statistics, this 33-minute tutorial is the way to go.
Some course benefits include:
- As far as beginner-friendly training goes, this is one of the best statistics courses online because it is well-explained and has plenty of practice data sets.
- Important lessons on the empirical rule and how it can help you to make forecasts about your data.
- Vital strategies on variability, namely how to find outliers and calculate standard deviation, which can help with risk management. So this is also one of the best statistics courses on LinkedIn learning for making better business decisions.
In the first data set under the introduction to variability, there’s a small typo to watch out for that may be confusing. The good news is that it has already been addressed in the discussion forum, so that should clear any confusion there might be in that section.
4. Statistics with R – Beginner Level [Udemy]
Would you like to understand R for statistical analysis?
Then this is one of the best statistics courses on Udemy to also learn R programming on the side.
Some course highlights include:
- Learning how to find outliers in a data series. As a result, you’ll be able to easily and better determine the quality of your data before you use it.
- Many practical examples on building frequency tables and box plot diagrams for exploratory data analysis.
- Because of its huge range of data visualization techniques, this is the best statistics course online for visualization. You’ll learn about histograms, cumulative frequency charts, and cross-tables, among others.
However, the course only tackles univariate analysis and doesn’t cover multivariate analysis, which offers more reliable results. That said, it offers important statistical foundations to set you on your way to understanding complex topics.
5. Probability and Statistics: To p or not to p? [Coursera]
If you have a specific interest in making better decisions, be it in life or business, this course by the University of London is key.
You’ll learn about:
- How to quantify uncertainty from scenarios with seemingly unquantifiable variables. Consequently, you’ll be able to work with a wide range of data formats.
- Multivariate applications with real-life examples, making this one of the best statistics courses on Coursera for practice.
- A lively approach to teaching that is simple, hands-on, and paired with a witty sense of humor to enrich your learning experience.
There are a few problems to watch out for with the peer review homework instructions. In particular, the LaTeX equations in assignment 1 don’t display too well. It remains one of the best statistics courses online because the rest of the assignments are well laid out, and the matter has been addressed in the forum.
6. SPSS Statistics Essential Training [LinkedIn Learning]
Are you interested in learning how to use IBM SPSS?
This data analysis and management tool is great for simply executing complex data manipulation.
Some course highlights include:
- A non-mathematical approach to SPSS where you don’t have to learn programming languages for data science. This is therefore the best statistics course on LinkedIn Learning if you don’t have a coding or math background.
- Learning data visualization techniques, and how to share descriptive statistics with other members of your team so they can reap the same benefits.
- Important data wrangling methods, so you can better process raw data to make it clean and reliable before you feed it to SPSS.
Because of its non-mathematical approach, it may not be suitable if you’d like to learn advanced statistical concepts and calculations. However, it simplifies all the statistical work involved in learning SPSS and descriptive statistics.
7. Python for Statistical Analysis [Udemy]
Would you like to perform statistical analysis in Python?
With an ability to handle large datasets with ease, Python is an excellent programming language for statistical analysis.
Some course highlights include:
- Bonus content on graphical exploration and how to integrate it with visual output to create outstanding presentations, articles, and reports.
- With a focus on connecting real-world problems with strategic examples, this is the best statistics course online for applied statistics through Python.
- Extra content on using Python for hypothesis testing, including tips on how to efficiently implement these tests using the latest libraries.
This course assumes an understanding of Python basics, and as such doesn’t go into great detail about the coding. For intermediate Python programmers, this is the best statistics course on Udemy to harness your knowledge of Python and explore complex machine learning and statistics projects.
8. Python and Statistics for Financial Analysis [Coursera]
Python is today commonly used by data scientists all around the world. This tutorial gives you insight into financial analysis through Python programming.
Some course benefits include:
- Building highly-reliable trading models, thanks to a multiple linear regression approach that considers a huge range of investment indicators.
- As far as data wrangling is concerned, this is one of the best statistics courses online. This knowledge will help you verify the quality and usefulness of data.
- Pointers on using Jupyter Notebook to practice your Python coding directly and bypass all client application installations that you’d normally need to carry out.
On the downside, this may not be the most ideal introductory training as you need some Python programming training to fit in comfortably.
The upside is that with just a little experience with Python basics, it is the best statistics course on Coursera to learn advanced concepts of financial analysis in no time.
9. Everyday Statistics, with Eddie Davila [LinkedIn Learning]
Learning statistics isn’t always about making huge business decisions. Sometimes it’s about solving everyday challenges like being good at certain games.
This is one of the best statistics courses on LinkedIn Learning because:
- It covers how to perform data analytics for better supply chain management, to improve stocking decisions, deliveries, and other aspects to avoid expensive disruptions.
- You’ll master how to use the ubiquitous bell curve to assess the risk of business projects by analyzing security returns.
- It is periodically updated to add new applications of statistics in everyday life so it offers great value.
If you’re keen on a certificate of completion, it’s worth noting that this course doesn’t offer one as it’s an ongoing series. The great thing is that it is the best statistics course online for staying up to date because you get to consistently learn new statistics concepts.
10. Statistics for Business Analytics and Data Science A-Z TM [Udemy]
Statistics is an important building block for data science and business analytics, and this course is great to get you started.
Some course highlights include:
- Learning how to use the Z-score and the standard normal Z-table for data analysis through advanced hypothesis testing.
- Having been recently updated, this is one of the best statistics courses on Udemy if you’d like to stay on top of the latest data analytics tools for data scientists and business analysts.
- Learning about the most important theorems of statistics, namely the Central Limit Theorem, for extracting additional information from business events.
While the course could have benefited from more slides to accompany the instructor’s audio and make some of the sections more interactive, it remains one of the best statistics courses online because you can still use the transcripts to get lesson summaries.
11. Bayesian Statistics: From Concept to Data Analysis [Coursera]
For the complete walkthrough on the Bayesian approach to inferential statistics, this training will take you from basic to advanced in no time.
At the end of this course, you’ll be able to:
- Carry out vital Bayesian statistics through hands-on exercises that cut across both Excel and R, thereby making this one of the best statistics courses on Coursera for data science versatility.
- Understand the differences between Bayesian & Frequentist statistics, what each approach has to offer, and when it’s suitable to use each one.
- Perform Bayesian analysis for both continuous and discrete data, so you’ll be able to work with a huge range of data formats.
Unfortunately, this may not be a beginner-friendly course as it assumes a basic understanding of probability and statistics. For intermediate learners, you’ll find that the course proceeds at an excellent pace without stalling on the basics.
12. Python Statistics Essential Training [LinkedIn Learning]
Via Python 3.6, this course will show you how to leverage the power of programming to speed through the basics of traditional statistics.
You’ll learn about:
- Vital principles for importing and cleaning data from various sources. This comes with an example of how to carry out these actions through personal email analytics.
- Describing and visualizing data by plotting quantitative variables, with more examples to reinforce the concept, making this the best statistics course on LinkedIn Learning for hands-on learning.
- Statistical modeling and how to perform goodness-of-fit tests, which can help establish patterns in data and determine future trends.
With Python now in version 3.8, the coding syntax has changed a little since the version used in this course. But it’s nothing too major that you can’t easily workaround, so it remains the best statistics course online for Python and data science.
13. Become a Probability & Statistics Master [Udemy]
If you’re looking to study statistics and probability for an upcoming exam, this tutorial offers the right training to get you test-ready.
Some course benefits include:
- From middle school math to advanced college calculus, the superb teaching style makes this one of the best statistics courses online no matter your level of education.
- Tons of review material at the end of each course topic to summarize every section’s most important highlights for speed reading later on.
- You get access to more than 600 practice questions, with 45 solved quizzes to show you the way.
Even though the training doesn’t use real-life data sets, you may still be able to derive many concepts for business applications. Conversely, it’s the best statistics course on Udemy if you’re more interested in curriculum statistics for passing institutional exams.
14. Probability Theory, Statistics and Exploratory Data Analysis [Coursera]
How does the probability theory affect data science?
This course will give you answers to this question and more. You’ll also get to learn about:
- Calculating correlation and visualizing data with Python so you also gain experience in an important programming language for your career.
- Random variables as the core concept of the training. As a result, you’ll be able to perform random experiments more accurately and efficiently.
- Being course 4/4 in the Master of Data Science program by HSE University, this is the best statistics course online to earn the credentials to land your first data science job.
There are lots of quizzes in between lectures which makes this course a little more time-consuming than it appears to be. However, it is for this reason that this is the best statistics course on Coursera if you’re keen on a course that gives you plenty of opportunities to practice.
15. Machine Learning & AI Foundations: Linear Regression [LinkedIn Learning]
If you’re interested in learning artificial intelligence and machine learning, in particular, this is the course to take you right to the heart of the statistics involved.
Some course highlights include:
- A detailed look at SPSS customization to make the most of every regression feature. This is therefore among the best statistics courses on LinkedIn Learning to learn regression via IBM SPSS.
- Using the Chart Builder to create scatter plots so you can track trends over time and evaluate performance, among other parameters.
- You also get to learn how to work with multilinear regression and what corrective measures you can take in case of collinearity.
Prior exposure to IBM SPSS statistics is assumed so you may have to bridge this course with a tutorial on SPSS. However, you can still comfortably take it regardless of this knowledge because it mostly focuses on the concepts rather than the software’s mechanics.
Conclusion
Learning statistics enables you to take on many data science roles.
You can accomplish all of your goals with the best statistics courses online for data science in 2023.
If business intelligence is a big motivator, then you may find that this Statistics for Data Science and Business Analysis course on Udemy is full of important statistical techniques for real business applications.
The training also covers inferential statistics to help predict business trends.
For a more holistic and diverse approach to learning statistics, you could try out the Introduction to Statistics course on Coursera.
Here, you’ll learn about statistical concepts, such as regression diagnostics, which you can put to good use across the board.
Lerma is our expert in online education with over a decade of experience. Specializing in e-learning and e-courses. She has reviewed several online training courses and enjoys reviewing e-learning platforms for individuals and organizations.