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https://github.com/pb319/multivariate_procedures_with_r
It is a 12-Weeks NPTEL course taught by Prof. Shalabh who is a Professor of Statistics and Data Science at IIT Kanpur. Course Description is availbe - https://onlinecourses.nptel.ac.in/noc24_mg68/preview
https://github.com/pb319/multivariate_procedures_with_r
Last synced: 2 months ago
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It is a 12-Weeks NPTEL course taught by Prof. Shalabh who is a Professor of Statistics and Data Science at IIT Kanpur. Course Description is availbe - https://onlinecourses.nptel.ac.in/noc24_mg68/preview
- Host: GitHub
- URL: https://github.com/pb319/multivariate_procedures_with_r
- Owner: pb319
- Created: 2024-03-26T23:15:14.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-05-11T14:02:23.000Z (8 months ago)
- Last Synced: 2024-05-12T07:35:28.416Z (8 months ago)
- Language: R
- Size: 94.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Multivariate_Procedures_with_R
It is a 12-week NPTEL course taught by Prof. Shalabh who is a Professor of Statistics and Data Science at IIT Kanpur. Course Description is available - [Here](https://onlinecourses.nptel.ac.in/noc24_mg68/preview)
#### Table of Contents:
- [Week 1](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-1)
- [Week 2](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-2)
- [Week 3](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-3)
- [Week 4](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-4)
- [Week 5](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-5)
- [Week 6](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-6)
- [Week 7](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-7)
- [Week 8](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-8)
- [Week 9](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-9)
- [Week 10](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-10)
- [Week 11](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-11)
- [Week 12](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#week-12)
- [Live Discussion](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#live-interaction)
- [Weekly Assignment Scores](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#weekly-assignment-scores)
- [Final Course Certificate](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#certificate-)
- [Handwritten Notes](https://drive.google.com/file/d/1ndEM3lqHQbbhClAHAmne1GwqRcHGPQhW/view)
****
#### **Week 1:**
- **Description:**
- Here We dealt with basic R syntax which will enable us to carry out our Multivariate Analysis with R easily in the long run. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=18&lesson=23).
- **Topics Covered:**
- R Installation
- Seeking Help in R
- Using R as a basic calculator
****
#### **Week 2:**
- **Description:**
- Here We dealt with the implementation of basic measures of central tendency, dispersion, etc. along with handling data with data vectors, matrix() function in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=20&lesson=31).
- **Topics Covered:**
- Introduction to Data Vectors
- Logical Operators
- Matrix Data Structure
- Measures of Central Tendency
- Measures of Dispersion
***
#### **Week 3:**
- **Description:**
- Here We shall be dealing with the techniques to handle missing(NA) values in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=28&lesson=52).
- **Topics Covered:**
- Basic Descriptive Statistics
- Handling Missing Value
- Measures of Central Tendency (With Missing Value)
- Measures of Dispersion (With Missing Value)
***
#### **Week 4:**
- **Description:**
- Here We shall be dealing with the techniques to handle missing(NA) values in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=29&lesson=56).
- **Topics Covered:**
- Introduction to Dataframes
- Simple and Grouped Boxplot
- Simple and Multiple Bar Diagram
- Grouped and Multiple Histogram
- Scatter Plot and Variation
- Matrix Scatter Plot
***
#### **Week 5:**
- **Description:**
- Here We dealt with the implementation of few diagrams to represent 3D and More Dimentional Data like, 3D Plot, Starts, and Chernoff Faces along with Normal Distribution in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=30&lesson=61).
- **Topics Covered:**
- 3d Plot
- Star Plot
- Chernoff Faces
- Normal Distribution (PDF, CDF, Quantiles)
***
#### **Week 6:**
- **Description:**
- Here We dealt with sampling distributions like Chi Square, t, F along with Estimation through Multivariate Normal in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=35&lesson=80).
- **Topics Covered:**
- Introduction to Multivariate Normal
- Chi-Square Distribution, t, F
- Estimation of Parameter
- Introduction to Point and Interval Estimation
- Estimation using MLE on Multivariate Normal Parameters
***
#### **Week 7:**
- **Description:**
- In this section, the focus was on building the foundation for the 'Testing of Hypothesis' to extend the same into multivariate cases in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=36&lesson=86).
- **Topics Covered:**
- Introduction to Hypothesis Testing
- Type1 and Type2 Errors
- P-value, Critical Value and Interval Method of Hypothesis Testing
- Central Limit Theorem
- Test for One Sample Mean (Sigma known and unknown)
- Paired Test
- Testing Hypothesis for Difference of Means (Independent Samples)
- Analysis of Variance (ANOVA)
- Homogeneity of Variance (Bartlett Test)
***
#### **Week 8:**
- **Description:**
- In this section, the focus was on building the foundation for the 'Testing of Hypothesis' to extend the same into multivariate cases in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=37&lesson=95).
- **Topics Covered:**
- Tests for Mean Vector with Multivariate Data (One Sample)
- Hotelling T-Square Statistic (Unknown Covariance Matrix)
- Tests for Mean Vector with Multivariate Data (Two Samples)
- Scaling of Data (Standardization/ Z- Score)
- Introduction to Multiple Linear Regression
- Assumptions, Estimation of Parameters (OLS, MLE)
- Gauss-Markov Theorem
***
#### **Week 9:**
- **Description:**
- In this week we dig deeper into Ression Analysis in R with Introduction to Classification. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=37&lesson=99).
- **Topics Covered:**
- Multiple Linear Regression Model Fitting
- Test of Hypothesis for Regression Coeffiients
- Confidence Interval estimation of Regression Coeffiients
- Test of Overall Adequecy of the Model using ANOVA
- Introduction to Multiple Linear Regression
- Godness of Fit
- Testing of Normality
- Logistic Regression
- Introduction to Classification
***
#### **Week 10:**
- **Description:**
- In this week we dig deeper into various procedures of Supervised Classification with implementation in R ending with an introduction to Clustering. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=39&lesson=112).
- **Topics Covered:**
- Bayes Procedure for Classification
- Classification Procedure for Multivariate Normal Distributions
- Dicriminant Function
- Confusion Matrix
- Introduction to Cluster Analysis
- Classification Schemes
- Agglomerative and Divisive Approach
***
#### **Week 11:**
- **Description:**
- In this week we dig deeper into various procedures of Unsupervised Classification with implementation in R ending with an introduction to Principal Component Analysis. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=40&lesson=116).
- **Topics Covered:**
- Hierarchical Clustering
- Dendograms and Visualisation
- Elbow Method
- Average Silhouette Method
- Implementation in R (using USArrests dataset)
- Introduction to Principal Component Analysis
***
#### **Week 12:**
- **Description:**
- Lastweek deals with Principal Component Analysis and Canonical Forms with Implementation in R. Course reference - [Click Here](https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=41&lesson=120).
- **Topics Covered:**
- Foundation of PCA
- Hands on with and without using packages
- Scree-Plot
- Introduction to Canonical Variables
- Statistical Analysis of Canonical Variable
#### **Live Interaction**
- **Description:**
- There was a live interaction with the course instructor which was truly fruitful and addressed some core doubts after the advent of Artificial Intelligence. Link - [Click Here]([https://onlinecourses.nptel.ac.in/noc24_mg68/unit?unit=41&lesson=120](https://www.youtube.com/watch?v=GYPQX0mIvWM)).
***
### Weekly Assignment Scores:
### **Certificate :**
> - The application of the above learnings can be found in my another project. Link - [Click Here](https://github.com/pb319/IPL_Sports_Magazine/tree/main/Predictive%20Analytics)
> - The explanation of the same is aviable in one of my Linkedin post ([link](https://www.linkedin.com/posts/pranaybiswas_resumeprojectchallenge10-resumeprojectchallenge10-activity-7188440262627471362-Ucpx?utm_source=share&utm_medium=member_desktop))
> - [Final Linkedin Post](https://github.com/pb319/Multivariate_Procedures_with_R?tab=readme-ov-file#certificate-)