Our ever-expanding Data Analyst in R path has two new courses today, and they’re all about helping you learn statistics using R.
Statistics Fundamentals in R and Probability Fundamentals in R are brand-new interactive courses that will build on the R programming skills you’ve developed in previous courses while teaching you key concepts from statistics and probability.
Learning this math is critical for effective data science work, because being able to execute something in code isn’t the same as understanding how it works. To make the right decisions and ensure your analysis is measuring what you want it to measure, you need to have a solid grasp of statistics and what’s happening to your data “under the hood” of your code.
But don’t worry — just because it’s math doesn’t mean it has to be painful! Like all Dataquest courses, these new courses are interactive and they’ll teach you statistics and probability through R programming while you analyze real-world data sets to solve realistic data science problems.
What Will I Learn in Statistics Fundamentals in R?
In Statistics Fundamentals in R, you’ll learn to ask better questions and make more informed decisions about how to analyze your data. You’ll learn to find hidden patterns using statistical methods, and you’ll learn how to implement everything through R programming so that it fits into your existing data science workflow.
Specifically, you’ll start by learning about sampling, and taking a closer look at how to perform stratified sampling and cluster sampling. Then you’ll study what variables are in statistics, and learn about the different scales used to measure them.
Next, it’s on to frequency distributions, absolute and relative frequencies, grouped frequency distributions, and percentiles. You’ll learn about these concepts and practice using them to identify patterns in your data, make comparisons across categories, and make massive data sets more manageable. You’ll also learn to use various visualizations, like grouped bar plots, step histograms, kernel density plots, and more to compare frequency distributions and better understand the patterns in your data.
Throughout the course, you’ll be analyzing real-world sports data from the WNBA. Then, once you’ve worked through all of the major concepts, you’ll be challenged to put all of your new R statistics skills together to build a guided project analyzing movie ratings on Fandango.
After completing the course, you will feel comfortable sampling data using a variety of methods. You’ll have built a better understanding of data structures, and you’ll be comfortable creating, visualizing, and comparing frequency distribution tables.
What Will I Learn in Probability Fundamentals in R?
In Probability Fundamentals in R, you’ll deepen your statistics skills by diving into probability as you analyze data about the lottery.
Working through the course, you’ll use your R programming skills and the statistics knowledge you’re learning to estimate empirical and theoretical probabilities. You’ll learn the fundamental rules of probability, and then work to solve increasingly complex probability problems.
You’ll also learn about independence in probability, which is an important concept to understand for some types of data science modeling.
Finally, you’ll be challenged to put all of your new skills and your R programming to the test to design the functionality of a mobile app that might help people give up gambling addictions by providing them with accurate information about the probability of winning the lottery under a variety of different circumstances.
By the end of the course, you’ll be capable of calculating the probabilities for random experiments and using the combination and permutation formulas to count the number of potential outcomes. You’ll also be able to set up basic simulations and use those to calculate probabilities.
Why Learn With Dataquest?
There are lots of places to learn statistics and probability, but learning with Dataquest offers some specific advantages.
First, we teach interactively, asking you to apply new concepts using your R coding skills and checking your work on every screen. That means you’ll get instant feedback on whether you’ve really understood what you’re learning, and you’ll also be simultaneously reinforcing your R skills as you build your expertise in statistics.
We also use real-world data and teach by asking you to solve realistic data science problems. For many students this makes learning on Dataquest more interesting and engaging than working through abstract sample problems or reading formulas in a textbook. The more interested you are in what you’re doing, the more likely you are to stick with it. That’s why we work hard to make our courses feel interesting and relevant to your data analysis goals.
Charlie is a student of data science, and also a content marketer at Dataquest. In his free time, he’s learning to mountain bike and making videos about it.
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