Data Analysis
Course Description:
The knowledge and abilities you gain in this course will qualify you for introductory-level data analyst positions. In this course, you’ll learn about the programming language known as R. You’ll learn the ins and outs of RStudio, the R programming language’s integrated development environment. R packages and other R-specific software applications and tools will also be covered in this course.
Recommended Books:
- Ross, S.M., 2017. Introductory statistics. Academic Press. ISBN 0128043172
- Goh E, Hui M. Learn R for Applied Statistics With Data Visualizations. Regressions, and Statistics, Business Media New York. 2019. ISBN 978-1-4842-4199-8 e-ISBN 978-1-4842-4200-1
- Hothorn T, Everitt BS. A handbook of statistical analyses using R. Chapman and Hall/CRC; 2014 Jul 20. ISBN: 1482204592
For extra practice:
Prerequisite:
Nil
Week wise Lecture Plan:
Topic | Detail |
1st & 2nd Week | |
Introduction to Data Analysis | Course Overview
Introduction to Data Analysis Basics Data collection Population vs sampling Random sampling Data types |
Introduction to R | Introduction to R
Installing R Data Objects in R Data Import and Export Basic Data Manipulation Computing with Data |
Quiz | |
Assignment | |
3rd & 4th Week | |
Summarizing and Describing Data | Simple summary statistics (Frequency Tables & Graphs)
Describing trends in data Mean (Variance & Standard deviation) Median, Mood Quartiles Data distributions |
Graphical Display using R | Data visualization plots
Boxplot, Histogram, Scatterplot, Heatmap, Barplot, Density plots Multi-plots |
Quiz | |
Assignment | Practice exercise of Data visualization using R on case study data |
5th, 6th & 7th Week | |
Probability | Sample Space and Events
Properties of Probability Conditional Probability Bayes Theorem |
Simple Inference
Conditional Inference |
Student t-test
Paired t-test χ2- test Fisher’s Exact Test |
Quiz | Regarding Lecture |
Assignment | Practice on Mortality and Water Hardness data |
8th & 9th Week | |
Analysis of Variance (ANOVA) | |
Visualization of statistical tests and ANOVA results with R | |
Quiz | Regarding Lecture |
Assignment | |
10th, 11th & 12th Week | |
Multivariate Analysis of Variance (MANOVA)+
Correlation + Covariance |
|
Quiz | Regarding Lecture |
Assignment | |
Hands-on Data Analysis | Foster Feeding of Rats of Different Genotypes +
Male Egyptian Skulls |
13th, 14th &15th Week | |
Simple Linear Regression
Multiple Linear Regression Logistic Regression & Linear Model |
|
Quiz | Regarding Lecture |
Assignment | |
Hands-on Data Analysis | Student performance data +
Linear model fitting on Microarray data |
16th, 17th, 18th Week | |
Clustering | Introduction to clustering
K-mean, Hierarchical clustering |
Introduction to python
|
Introduction to python
Data Objects in python Data Import and Export Basic Data Manipulation Computing with Data Hands-on with Jupiter notebook |
Quiz | Regarding Lecture |
Assignment | |
Hands-on Analysis | |
19th & 20th Week | |
Introduction to Machine Learning | Overview, Supervised Learning & applications |
Python for Machine Learning | Python for Machine Learning • numpy • matplotlib • pandas • scipy • scikit |
21st, 22nd, 23rd & 24th Week | |
Simple Linear Regression
Multiple Linear Regression |
Using python |
Supervised learning Approaches | Introduction to Supervised Learning
Decision Trees Random Forest |
Unsupervised learning approaches | |
Quiz | Regarding Lecture |
Assignment | |
Hands-on Data Analysis | Financial and Economic Data |
25th & 26th Week | |
Data Classification and Dimensionality Reduction techniques | |
Principal Component Analysis | |
Quiz | Regarding Lecture |
Assignment | |
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Versutum
Requirements
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Features
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Target audiences
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