FeaturedUdemy
Introduction to Statistics in R
4.8(2,090)131k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
R was designed ground-up for statistical computing and data analysis. This intermediate course leverages R's native statistical routines and dplyr package to analyze real sales data, calculate probability distributions, measure correlation, and conduct formal hypothesis testing.
Who It's For
R users, data analysts, and researchers looking to solidify their understanding of probability, summary statistics, and study design using R.
Key Takeaways
- Descriptive Statistics in R: Compute summary metrics (mean, median, standard deviation, quantiles) across data vectors and DataFrames.
- Probability Distributions: Model continuous and discrete random variables using R's built-in distribution functions (norm, binom, etc.).
- Correlation & Visualization: Measure linear association and visualize relationship trends with scatter plots and trendlines.
- Hypothesis Testing: Design statistical experiments, calculate test statistics, and interpret confidence intervals and p-values.
About this course
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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