Course Content of Basic Data Analysis with R Programming
Chapter 1 Problem Solving Using Computer
- Problem Analysis
- Algorithm Development & Flow charting
- Compilation and Execution
- Debugging and Testing
- Program Documentation
Chapter 2 Introduction to C Programming
- Character set, Keywords and data types
- Preprocessor and directives
- Constants and Variables
- Operators and statement
- Formatted I/O
- Character I/O
- Programs Using I/O statement
Chapter 3 Control statements
- Introduction
- The goto, if, if….else, switch statements
- The while, do…while, for statements
Chapter 4 User-Defined Functions
- Introduction
- Function definition and return statement
- Function prototypes
- Function invocation, Call by value & Call by reference, Recursive Functions
Chapter 5 Arrays and Strings
- Defining an array
- One dimensional arrays
- Multi-dimensional arrays
- Strings and string manipulation
- Passing array and string to function
Basic Data Analysis with R Programming Course Outline (1.5 Months)
Basic Data Analysis with R
Interface of R and RStudio
Data types and indexing (assignments, objects, vectors, matrices, data frames, lists)
R built in functions and syntax
Working directory
Packages
Importing data from CSV, Excel, .txt, SPSS, Stata files etc…
Exporting data as CSV
Preparing data for analysis (renaming variables, variable types, missing values)
Computing, transforming and recoding variables
Subset datasets by row and by columns
Descriptive statistics, frequency tables, cross tabulation tables
Graphics (boxplot, histogram, scatterplot, partitioning window)
Basic analyses (t-test, correlation, ANOVA, regression, chi-square)
Review of data types
Sub-setting datasets
Sorting datasets
Reshaping datasets
Merging and appending datasets
Aggregating datasets (statistics by group, using the suite of apply functions)
User written functions (syntax, if/else statements)
Loops (for loop, while loop, repeat loop)
Base plot function
Graphs for quantitative data (boxplots, scatterplots, bar graphs, histograms etc…)
Changing graph elements: titles, point size, colors
Extensive use of ggplot2