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R Programming for Statistics and Data Science


Introduction :
Ten Things You Will Learn in This Course

Getting started :
Intro
Downloading and installing R & RStudio
Quick guide to the RStudio user interface
RStudio's GUI
3 questions
Changing the appearance in RStudio
Installing packages in R and using the library

The building blocks of R :
Creating an object in R
Exercise 1 Creating an object in R
Data types in R - Integers and doubles
Data types in R - Characters and logicals
Objects and Data Types
4 questions
Exercise 2 Data types in R
Coercion rules in R
Exercise 3 Coercion rules in R
Functions in R
Exercise 4 Using functions in R
Functions and arguments
Exercise 5 The arguments of a function
Building a function in R (basics)
Objects and Functions
3 questions
Exercise 6 Building a function in R
Using the script vs. using the console

Vectors and vector operations :
Intro
Introduction to vectors
Vector recycling
Exercise 7 Vector recycling
Naming a vector in R
Exercise 8 Vector attributes - names
Introduction to vectors
2 questions
Getting help with R
Getting Help with R
2 questions
Slicing and indexing a vector in R
Extracting elements from a vector
3 questions
Exercise 9 Indexing and slicing a vector
Changing the dimensions of an object in R
Exercise 10 Vector attributes - dimensions

Matrices :
Creating a matrix in R
Faster code: creating a matrix in a single line of code
Creating a matrix
3 questions
Exercise 11 Creating a matrix in R
Do matrices recycle?
Indexing an element from a matrix
Slicing a matrix in R
Exercise 12 Indexing and slicing a matrix
Matrix arithmetic
Exercise 13 Matrix arithmetic
Matrix operations in R
Matrix operations
4 questions
Exercise 14 Matrix operations
Categorical data
Creating a factor in R
Factors in R
2 questions
Exercise 15 Creating a factor in R
Lists in R
Exercise: Lists in R
Completed 33% of the course

Fundamentals of programming with R :
Relational operators in R
Logical operators in R
Vectors and logicals operators
Relational and Logical operators in R
5 questions
Exercise Logical operators
If, else, else if statements in R
Exercise If, else, else if statements in R
If, else, else if statements - Keep-In-Mind's
For loops in R
Exercise: For Loops in R
While loops in R
Exercise: While loops in R
Repeat loops in R
Loops in R
4 questions
Building a function in R 2.0
Building a function in R 2.0 - Scoping
Exercise Scoping
Completed 50% of the course

Data frames :
Intro
Creating a data frame in R
Exercise 16 Creating a data frame in R
The Tidyverse package
Data import in R
Importing a CSV in R
Data export in R
Exercise 17 Importing and exporting data in R
Creating data frames
5 questions
Getting a sense of your data frame
Indexing and slicing a data frame in R
Data frame operations
4 questions
Extending a data frame in R
Exercise 18 Data frame operations
Dealing with missing data in R

Manipulating data :
Intro
Data transformation with R - the Dplyr package - Part I
Data transformation with R - the Dplyr package - Part II
Sampling data with the Dplyr package
Using the pipe operator in R
Manipulating data
5 questions
Exercise 19 Data transformation with Dplyr
Tidying data in R - gather() and separate()
Tidying data in R - unite() and spread()
Tidying data
5 questions
Exercise 20 Data tidying with Tidyr

Visualizing data :
Intro
Intro to data visualization
Intro to ggplot2
Variables: revisited
Building a histogram with ggplot2
Exercise 21 Building a histogram with ggplot2
Building a bar chart with ggplot2
Exercise 22 Building a bar chart with ggplot2
Building a box and whiskers plot with ggplot2
Exercise 23 Building a box plot with ggplot2
Building a scatterplot with ggplot2

Exploratory data analysis :
Population vs. sample
Mean, median, mode
Skewness
Exercise 25 Determining Skewness
Variance, standard deviation, and coefficient of variability
Covariance and correlation
Exercise 26 Practical example with real estate data

Hypothesis Testing :
Distributions
Standard Error and Confidence Intervals
Hypothesis testing
Type I and Type II errors
Test for the mean - population variance known
Exercise: Test for the mean - population variance known
The P-value
Test for the mean - Population variance unknown
Exercise: Test for the mean - population variance unknown
Comparing two means - Dependent samples
Exercise: Comparing two means - Dependent samples
Comparing two means - Independent samples

Linear Regression Analysis :
The linear regression model
Correlation vs regression
Geometrical representation
First regression in R
How to interpret the regression table
Exercise: Doing a regression in R
Decomposition of variability: SST, SSR, SSE
R-squared
Completed 100% of the course