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Introduction to Statistics in R

IntermediateSkill Level
4.7+
1,904 reviews
Updated 05/2026
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
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RProbability & Statistics4 hr15 videos54 Exercises4,250 XP120K+Statement of Accomplishment

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Course Description

Statistics is the study of how to collect, analyze, and draw conclusions from data. It’s a hugely valuable tool that you can use to bring the future into focus and infer the answer to tons of questions. For example, what is the likelihood of someone purchasing your product, how many calls will your support team receive, and how many jeans sizes should you manufacture to fit 95% of the population? In this course, you'll use sales data to discover how to answer questions like these as you grow your statistical skills and learn how to calculate averages, use scatterplots to show the relationship between numeric values, and calculate correlation. You'll also tackle probability, the backbone of statistical reasoning, and learn how to conduct a well-designed study to draw your own conclusions from data.The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos. The course glossary can be found on the right in the resources section. To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

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What you'll learn

  • Assess event probabilities with R functions and Recognize the defining parameters of uniform, binomial, normal, Poisson, exponential, and t distributions
  • Differentiate measures of center and spread and Evaluate their suitability in the presence of skewness or outliers
  • Distinguish between controlled experiments and observational studies, Assess potential confounding, and Recognize why correlation alone does not establish causation
  • Evaluate the impact of sampling methods and sample size on sampling distributions, applying the Central Limit Theorem to Assess estimation accuracy
  • Identify data types and Recognize suitable summary statistics and visualizations for each in R

Prerequisites

Data Manipulation with dplyr Intermediate R
1

Summary Statistics

Summary statistics gives you the tools you need to boil down massive datasets to reveal the highlights. In this chapter, you'll explore summary statistics including mean, median, and standard deviation, and learn how to accurately interpret them. You'll also develop your critical thinking skills, allowing you to choose the best summary statistics for your data.
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2

Random Numbers and Probability

3

More Distributions and the Central Limit Theorem

It’s time to explore one of the most important probability distributions in statistics, normal distribution. You’ll create histograms to plot normal distributions and gain an understanding of the central limit theorem, before expanding your knowledge of statistical functions by adding the Poisson, exponential, and t-distributions to your repertoire.
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4

Correlation and Experimental Design

In this chapter, you'll learn how to quantify the strength of a linear relationship between two variables, and explore how confounding variables can affect the relationship between two other variables. You'll also see how a study’s design can influence its results, change how the data should be analyzed, and potentially affect the reliability of your conclusions.
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Introduction to Statistics in R
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FAQs

Is this course suitable for beginners?

Yes, this course is suitable for beginners. It is designed to equip you with the expertise you need to use sales data and develop your statistical skills and knowledge while introducing essential concepts like mean, median, and standard deviation, probability, and correlation.

What types of data does this course cover?

This course covers sales data, probability, and correlation, as well as other key concepts like mean, median, and standard deviation.

Who will benefit from this course?

Professionals in marketing, product, accounting, and finance role would benefit from having knowledge about statistics. Also, anyone wanting to learn about how to draw conclusions from data or make data-driven decisions in the workplace would benefit from this course.

How can I use summary statistics to draw my own conclusions?

Summary statistics such as mean, median and standard deviation provide you with a way to become more familiar with data and discover what it can tell you. By using this information to create histograms, and measure the strength of linear relationships, you can draw conclusions about your data.

What is the Central Limit Theorem?

The Central Limit Theorem states that the sum of a large number of random samples drawn from any distribution will tend to be normally distributed, regardless of the underlying distribution of the population from which samples are drawn.

What topics are explored in the Correlation and Experimental Design chapter?

In this chapter, you'll explore how to quantify the strength of a linear relationship between two variables, how confounding variables can affect the relationship between two other variables, and how to study the design of a data set to determine the reliability of conclusions made from the data.

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