Path overview
In this path, you’ll learn the foundations of statistics such as sampling, working with variables, and understanding frequency distribution tables and the fundamentals of probability and how to use them for analysis. You’ll also learn how to create and test hypotheses with significance testing, and how to make forecasts based on patterns and trends with real-world data.
Best of all, you’ll learn by doing – you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.
Key skills
- Cleaning, preparing and analyzing data with R
- Creating insightful data visualizations
- Using statistics to perform descriptive analytics
- Using probabilities to perform predictive analysis
Path outline
Part 1: Probability and Statistics with R [5 courses]
Introduction to Statistics in R 5h
Objectives- Sample data using simple random sampling, stratified sampling, and cluster sampling
- Measure variables in statistics
- Build, visualize, and compare frequency distribution tables
Intermediate Statistics in R 3h
Objectives- Summarize a distribution using the mean, the weighted mean, the median, or the mode
- Measure the variability of a distribution using the variance and the standard deviation
- Compare values using z-scores
Introduction to Probability in R 2h
Objectives- Estimate theoretical and empirical probabilities
- Define the fundamental rules of probability
- Identify combinations and permutations
Conditional Probability in R 2h
Objectives- Assign probabilities based on conditions
- Assign probabilities based on event independence
- Assign probabilities based on prior knowledge
- Create spam filters using multinomial Naive Bayes
Hypothesis Testing in R 1h
Objectives- Implement probability density functions
- Create testable hypotheses
- Decide which hypotheses to support based on your data
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Projects in this path
Investigating Fandango Movie Ratings
For this project, you’ll be a data journalist analyzing Fandango’s movie ratings to determine if there was any change after a 2015 analysis found evidence of bias. You’ll use R and statistics skills to compare movie ratings data from 2015 and 2016.
Finding the Best Markets to Advertise In
For this project, we’ll assume the role of analysts at an e-learning company to determine the two best markets to advertise our programming courses in.
Mobile App for Lottery Addiction
For this project, you’ll take on the role of a data analyst at a medical institute, using probability and combinatorics in R to develop a mobile app that helps lottery addicts better estimate their chances of winning.
Building a Spam Filter with Naive Bayes
For this project, we’ll step into the role of data scientists to build a spam filter for SMS messages. We’ll apply conditional probability concepts and use the Naive Bayes algorithm in R.
Winning Jeopardy
For this project, we’ll assume the role of a Jeopardy contestant analyzing a dataset of past questions, using chi-squared tests and text analysis in R to identify common categories and develop optimal strategies.
Plus 0 more projects
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