ABOUT THE COURSE:The course entitled "Statistical Data Analysis with R" is a foundational course in statistical data analysis using R. It is beneficial for those who seeks career in data analytics or deals with data in academics or industry. This course covers all the important aspects of data analysis and the background statistical concepts in thorough manner. At the end of the course student will be able to deal with data organization, visualization, analysis, modeling of data and their presentation as dynamic document.INTENDED AUDIENCE: UG/PG students of all discipline, teachers, researchers and industry professionals.INDUSTRY SUPPORT: All companies that deals with data analysis
Overview
Syllabus
Week 1:
- Installation of R
- Introduction to R
- Introduction to R-studio and R-markdown.
- Data objects in R
- Creation of vector, numeric, logical, character and factor vector
- Creation of matrix and matrix operations.
- Concept of Online data frame
- Reading data from various sources
- Descriptive statistics
- Defining a new function in R
- Base graphics of R.
- Introduction to probability models in R
- Discrete probability distributions
- Continuous probability distributions
- Sampling distribution with R
- Central Limit Theorem (CLT)
- Law of large numbers
- Use of replicate() function
- Linear regression models
- Simple linear regression model
- Multiple linear regression models
- Model diagnostics
- Introduction to non-linear models
- Maximum likelihood estimation
- Fitting with optim() function.
- Hypothesis testing
- t.test, chisq.test
- ANOVA for CRD, RBD, and factorial analysis.
- Introduction to tidyverse packages
- ggplot2
- readr
- Data wrangling with dplyr.
- tibbles
- Concept of pipe operators
- select(), mutate(), filter() etc
- Introduction to time series in R.
- ts() object and plot.ts()
- decomposition of time series
- ACF and PACF
- Stationarity of time series
- Model fitting with auto.arima()
- Documentation with R
- rmarkdown
- bookdown
Taught by
Prof.Athar Ali Khan
