Data Science is a combination of statistics and computer science. There are thousands of resources and roadmaps to learn the computer science side of Data Science, but people often struggle to learn the statistics part. So, if you want to learn statistics for Data Science, this article is for you. In this article, I’ll take you through how to learn statistics for Data Science with learning resources.
Here’s How to Learn Statistics for Data Science
Below are the steps you should follow to learn statistics for Data Science:
- Understand the Fundamentals of Statistics
- Learn Inferential Statistics
- Learn Advanced Statistical Methods
- Work on Projects based on Statistical Analysis
Let’s go through these steps to learn Statistics for Data Science.
Understand the Fundamentals of Statistics
The first step is to understand the fundamentals of statistics you need for Data Science. Below are the essential topics you need to cover to understand the fundamentals of statistics:
- Descriptive Statistics (mean, median, mode, variance, standard deviation)
- Probability (basic concepts, probability distributions)
- Data Visualizations
Here’s a free course on Statistics by Udacity that will help you understand all these concepts.
Learn Inferential Statistics
The next step is to learn inferential statistics in detail. Although you will learn about inferential statistics in the free course I recommended above, try to dive deeper. Below are some essential topics you need to cover to understand inferential statistics:
- Hypothesis Testing (null and alternative hypotheses, p-values, t-tests, chi-square tests)
- Confidence Intervals
- ANOVA (Analysis of Variance)
Here’s a detailed course on Inferential Statistics you can follow to learn these topics and even more.
Learn Advanced Statistical Methods
The next step is to learn advanced methods required for statistical analysis. Below are the essential topics you need to cover:
- Linear Regression
- Multiple Linear Regression
- Logistic Regression
- Time Series Analysis
- Multivariate Analysis
The course I mentioned above on Inferential Statistics will help you learn regression analysis methods as well. And to learn Time Series and Multivariate Analysis, you can follow this free guide.
Work on Projects based on Statistical Analysis
Now, the next step is to use statistical concepts in solving problems by working on projects. Below are some projects you can work on to improve your statistical analysis concepts:
- Quantitative Analysis
- Statistical Modelling
- Hypothesis Testing
- Website Performance Analysis
- Multivariate Time Series Forecasting
Summary
So, below are the steps you should follow for learning statistics for Data Science:
- Understand the Fundamentals of Statistics
- Learn Inferential Statistics
- Learn Advanced Statistical Methods
- Work on Projects based on Statistical Analysis
I hope you liked this article on a guide to learning statistics for Data Science. Feel free to ask valuable questions in the comments section below. You can follow me on Instagram for many more resources.
