What Is R? - High-Level and Low-Level Languages - What Is Statistics? - What Is Data Science? - What Is Data Mining? - What Is Text Mining? - Natural Language Processing - Three Types of Analytics - Big Data - Why R? - What Is R? - The Integrated Development Environment- RStudio: The IDE for R - Installation of R and RStudio - Writing Scripts in R and RStudio- Basic Syntax- Descriptive Statistics- Reading data files – Basic Data Processing.

Data Visualizations - What Are Data Visualizations? - Bar Chart and Histogram - Line Chart and Pie Chart - Scatterplot and Boxplot - Scatterplot Matrix - Social Network Analysis Graph Basics - Using ggplot2 - What Is the Grammar of Graphics? - The Setup for ggplot2 - Aesthetic Mapping in ggplot2 - Themes in ggplot2 - ggplot2 Common Charts - Bar Chart - Histogram - Density Plot – Scatterplot - Line chart -Boxplot - Interactive Charts with Plotly and ggplot2.

Inferential Statistics and Regressions - What Are Inferential Statistics and Regressions? - apply(), lapply(), sapply() - Sampling - Simple Random Sampling - Stratified Sampling - Cluster Sampling – Correlations - Covariance - Hypothesis Testing and P-Value - T-Test - Types of T-Tests - Assumptions of T-Tests ----- Type I and Type II Errors- One-Sample T-Test - Two-Sample Independent T-Test ------ Two-Sample Dependent T-Test.

Creating variables and assigning data - Using vectors and factors - Using lists - Using data classes - Looping statements - Decision support statements – if | else - Using functions - Introduction to tidyverse - Installing and loading tidyverse - Loading and examining a dataset - Filtering a dataset - Grouping and summarizing a dataset - Plotting a dataset - Graphing burglaries by month and year

Loading a csv file with read.table() - Loading a csv file with read.csv() - Loading a tab delimited file with read.table() - Using readr to load data - Filtering records to create a subset - Narrowing the list of columns with select() - Arranging Rows - Adding Rows with mutate() - Summarizing and Grouping - Piping - Challenge - Gathering - Spreading - Separating - Uniting.