This course provides a practical guide using R and the tidyverse, guiding statistical concepts and analysis techniques.

Rp.tar.gz

datascience

Rlang

The world is full of data and it can be quite challenging to infer the knowledge based on statistical reasoning. This course aims to equip you with the skills you need to play with your data, wrangle it, and visualize it.  

Starting with data visualization, the course gets learners building ggplot2 graphs early on and then continues to reinforce important concepts graphically throughout the course. After moving through data wrangling and data importing, you’ll be introduced to modeling, which plays a prominent role, with a focus on building regression models and inference for regression. Lastly, statistical inference is presented through a computational lens with calculations done via the infer package.

By the end of this course, you’ll develop your data science toolbox, equipping yourself with tools such as data visualization, data formatting, data wrangling, and data modeling using regression.

Data-Centric Statistical Inference Using R and Tidyverse

How do you fit a linear regression model in `tidyverse`?

How do you fit a linear regression model in <code>tidyverse</code>?

The number of missing values in a variable

The number of unique values in a variable

The number of columns in the data frame



What's the `n_unique` column in the output of the `skim` function?

What’s the <code>n_unique</code> column in the output of the <code>skim</code> function?

The change in the response variable for each unit change in the predictor variable

The correlation between the predictor and response variables

What's the slope of a simple linear regression model?

What’s the slope of a simple linear regression model?

Which is an example of a numerical explanatory variable?



Which is an example of a numerical explanatory variable?

What's the formula for calculating residuals?



What’s the formula for calculating residuals?

The line that has the highest correlation coefficient

The line that has the lowest correlation coefficient



The line that minimizes the sum of the squared residuals

The line that maximizes the sum of the squared residuals

What's meant by the "best-fitting" line in regression?



What’s meant by the “best-fitting” line in regression?

It’s used to raise a number to the power of another number.

It’s used to indicate a model formula in the `lm()` function.

It’s used to compare two values for equality.

What does the tilde operator (`~`) do in R?

What does the tilde operator (<code>~</code>) do in R?

Statistics that describe the relationship between two variables

Statistics that describe the relationship between multiple variables

Statistics that describe the distribution of a single variable

Statistics that describe the distribution of multiple variables

What are univariate summary statistics?

Multiple choice questions

Multiple choice questions

Test yourself on the concepts of basic regression.

Getting Started with Data in R

Data Visualization

Data Wrangling

Data Importing and “Tidy” Data

Basic Regression

Multiple Regression

Statistical Inference with the infer Package

Bootstrapping and Confidence Intervals

Hypothesis Testing

Inference for Regression

Tell a Story with Data

Appendix

Test Your Skills on Basic Regression