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Introduction To Data Science Using R Programming
Introduction
Introduction (1:53)
Basics of R tool
Introduction to Course (6:01)
R programming installation and concepts (7:31)
R programming computations (9:16)
Basic Data Visualization
Data Visualization - Module (5:07)
Pie charts (8:15)
Bar charts (12:36)
Boxplots (10:19)
Histograms (7:15)
Line charts (7:29)
Scatterplots (10:14)
Case Study Basic data visualization (4:30)
Advanced Data Visualization
Advanced Data Visualization (2:22)
Basic Illustration of ggplot2 package (8:34)
Facetting (7:39)
Boxplots and Jittered Plots (4:24)
Histograms and Frequency Polygons (7:46)
Bar Charts and Time Series (12:58)
Basic Plot Types (8:10)
Case Study for ggplot2 package Scatterplot Encircling (7:44)
Surface Plots (7:33)
Revealing uncertainity (7:31)
Weighted data (9:12)
Drawing Maps- Vector Boundries (6:23)
Drawing Maps - Point Metadata (6:13)
Diamonds data for research (10:32)
Dealing with overlapping (8:41)
Statistical summaries (7:28)
Scatterplot from excel file (9:35)
Heatmap and area chart from excel file (9:19)
Various bar charts from excel file (10:27)
Leaflet Maps
Implementing Leaflet with R tool (5:48)
Adding Markers in map (4:33)
Popups and Labels (10:47)
Shiny Framework using Leaflet and R (9:14)
Statistics
Mean, median and mode (10:57)
Linear Regression (8:40)
Multiple Regression (9:27)
Logistic Regression (6:49)
Normal Distribution (9:38)
Binomial Distribution (6:31)
Poisson Regression (5:49)
Analysis of Covariance (8:15)
Time Series Analysis (10:06)
Case study Time Series from dataset (4:17)
Decision Tree (7:06)
Implementation of decision tree in Dataset (4:13)
Nonlinear Least Square (7:50)
Case Study- Random Forest (7:09)
Survival Analysis (7:10)
Data Manipulation
Case Study Exporting data in R (9:36)
Data Munging and Visualization (7:56)
Hierarchial Clustering (6:26)
K means clustering (7:49)
Basic Illustration of ggplot2 package
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