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In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

Course Curriculum

Section 1: Introduction
01_01-Introduction and course overview Details 00:35:00
01_02 About The Author Details FREE 00:20:00
01_03-Installing R And R Studio Details 01:00:00
01_04-Navigating R Studio Details 00:20:00
01_05-Packages Details 00:00:00
01_06-Assigning Variables Details 00:00:00
01_07-Numbers, Strings, And Booleans Details 00:00:00
01_08-Workspace Operations Details 00:00:00
01_09-How To Access Your Working Files Details 00:00:00
Section 2: Basic Operations And Manipulations
02_01-Basic Operators Details 00:20:00
02_02-Vectors Details 00:40:00
02_03-Sequences Details 00:30:00
02_04-Basic Statistical Functions Details 00:00:00
02_05-Matrices Details 00:00:00
02_06-Matrix Operations Details 00:00:00
02_07-Basic Matrix Statistics Details 00:00:00
02_08-Generating Random Numbers Details 00:00:00
02_09-String Functions Details 00:00:00
02_10-Dates And Times Details 00:00:00
Section 3: Plotting
03_01-Line Plots Details 00:00:00
03_02-Plotting Arguments Details 00:00:00
03_03-Bar Graphs And Histograms Details 00:00:00
03_04-Scatter Plots Details 00:00:00
03_05-Probability Plots Details 00:00:00
03_06-Combining And Saving Plots Details 00:00:00
Section 4: Working With Data
04_01-Arrays Details 00:00:00
04_02-Lists Details 00:00:00
04_03-Data Frames Details 00:00:00
04_04-Data Import Details 00:00:00
04_05-Missing Data Part 1 Details 00:00:00
04_06-Missing Data Part 2 Details 00:00:00
04_07-Ordering And Sorting Details 00:00:00
04_08-Subsetting And Indexing Details 00:00:00
4_09-Merging Data Details 00:00:00
04_10-Examining Files And Objects Details 00:00:00
Section 5: Data Analysis
05_01-Descriptive Statistics Details 00:00:00
05_02-Apply Functions Details 00:00:00
05_03-Linear Models Details 00:00:00
05_04-Extracting Model Information Details 00:00:00
05_05-Principal Componant Analysis Details 00:00:00
Section 6: Time Series Data
06_01-XTS Objects Details 00:00:00
06_02-ACF Plots Details 00:00:00
06_03-Decomposition Details 00:00:00
06_04-Exponential Smoothing Details 00:00:00
06_05-Rolling Functions Details 00:00:00
06_06-ARIMA Models Details 00:00:00
Section 7: Conditional Statements And Loops
07_01-If Statements Details 00:00:00
07_02-For Loops Details 00:00:00
07_03-While Loops Details 00:00:00
07_04-Appending Loops Details 00:00:00
Section 8: UserDefined Functions
08_01-Writing Functions Details 00:00:00
08_02-Debugging Functions Details 00:00:00
08_03-Recursive Functions Details 00:00:00
Section 9: Saving Data
09_01-Saving Different Types Of Data Details 00:00:00
09_02-Additional Resources Details 00:00:00
Section 10: Download Sample
10_01. Download Samples Details 00:00:00

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  • 80 Days
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