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Course10610484657 lectures

Exploratory Data Analysis for Data Science with R Software (English)

Prof. Shalabh · IIT Kanpur

Start with lecture 1 At NPTEL

Lectures

Week 1

  1. Lecture 0 : How to Learn and Follow the Course Video
  2. Lecture 1 : Data Science- Why, What and How? Video
  3. Lecture 2 : Introduction to R Software Video
  4. Lecture 3 : Calculations with R Software - Basics and R as a Calculator Video
  5. Lecture 4 : Calculations with R Software - Calculations with Data Vectors Video
  6. Lecture 5 : Calculations with R Software - Built-in Commands and Missing Data Handling Video
  7. Lecture 6 : Calculations with R Software - Operations with Matrices Video

Week 2

  1. Lecture 7 : Data Preparation - CSV and TXT Data Files Video
  2. Lecture 8 : Data Preparation - Excel Files and Data Frame Video
  3. Lecture 9 : Introduction to Exploratory Data Analysis - Objectives, Steps and Basic Definitions Video
  4. Lecture 10 : Introduction to Exploratory Data Analysis - Variables and Types of Data Video
  5. Lecture 11 : Frequency Distribution - Absolute, Relative and Cumulative Frequencies of Attribute and Discrete Data Video
  6. Lecture 12 : Frequency Distribution - Absolute, Relative and Cumulative Frequencies of Continuous Data Video

Week 3

  1. Lecture 13 : Frequency Distribution - Frequency Distribution with R Package Video
  2. Lecture 14 : Univariate Graphics and Plots - Bar Diagrams Video
  3. Lecture 15 : Univariate Graphics and Plots - Subdivided Bar Plots and Pie Diagrams Video
  4. Lecture 16 : Univariate Graphics and Plots - 3D Pie Diagram and Tree Map Video
  5. Lecture 17 : Univariate Graphics and Plots - Histogram, Kernel Density and Stem–Leaf Plots Video

Week 4

  1. Lecture 18 : Univariate Graphics and Plots - Graphics with ggplot2 Package Video
  2. Lecture 19 : Univariate Graphics and Plots - Creating Graphics with ggplot2 Package Video
  3. Lecture 20 : Univariate Graphics and Plots - Bar Diagram and Tree Map with ggplot2 Video
  4. Lecture 21 : Univariate Graphics and Plots - Grouped Bar and Scatter Diagrams with ggplot2 Package Video
  5. Lecture 22 : Univariate Graphics and Plots - Histogram, Dot Chart and Kernel Density Plots with ggplot2 Video

Week 5

  1. Lecture 23 : Central Tendency of Data- Arithmetic Mean Video
  2. Lecture 24 : Central Tendency of Data- Median Video
  3. Lecture 25 : Central Tendency of Data- Quantiles Video
  4. Lecture 26 : Central Tendency of Data- Mode Video
  5. Lecture 27 : Central Tendency of Data- Geometric Mean and Harmonic Mean Video

Week 6

  1. Lecture 28 : Variation in Data- Range, Interquartile Range and Quartile Deviation Video
  2. Lecture 29 : Variation in Data- Absolute Deviation and Absolute Mean Deviation Video
  3. Lecture 30 : Variation in Data- Mean Squared Error, Variance and Standard Deviation Video
  4. Lecture 31 : Variation in Data- Computation of Variance and Standard Error with R Video

Week 7

  1. Lecture 32 : Variation in Data- Coefficient of Variation and Summary Video
  2. Lecture 33 : Variation in Data- Box Plots and Violin Plots Video
  3. Lecture 34 : Moments- Raw, Central and Absolute Moments Video
  4. Lecture 35 : Moments- Computation of Moments in R Video

Week 8

  1. Lecture 36 : Moments - Skewness and Kurtosis Video
  2. Lecture 37 : Scaling of Data - Centering, Scaling and Z-Scores Video
  3. Lecture 38 : Association of Variables - Scatter and Smooth Scatter Plots Video
  4. Lecture 39 : Association of Variables - Line Chart, Time Series Plot and Bubble Chart Video

Week 9

  1. Lecture 40 : Association of Variables : Quantile - Quantile Plot Video
  2. Lecture 41 : Association of Variables : Three-Dimensional Plots, Heat Maps and Word Cloud Video
  3. Lecture 42 : Association of Variables : Correlation Coefficient Video
  4. Lecture 43 : Association of Variables : Correlation Coefficient using R Software Video

Week 10

  1. Lecture 44 : Association of Variables : Rank Correlation Coefficient Video
  2. Lecture 45 : Association of Variables : Measures of Association for Discrete and Counting Variables: Bivariate Frequency and Contingency Tables Video
  3. Lecture 46 : Association of Variables : Measures of Association for Discrete and Counting Variables with R Commands: Contingency Table, Chi-Squared Statistic, Cramer‘s V Statistic and Contingency Coefficient Video
  4. Lecture 47 : Modelling of Variables : Least Squares Method – One Variable Video

Week 11

  1. Lecture 48 : Modelling of Variables : Least Squares Method –More than One Variable and R Commands Video
  2. Lecture 49 : Handling Text Data : Basic Operations with Text and Strings Video
  3. Lecture 50 : Handling Text Data : Operations for Finding Patterns in Text Data with Pipe Operator Video
  4. Lecture 51 : Handling Text Data : Operations for Finding Patterns in Text Data without Pipe Operator Video

Week 12

  1. Lecture 52 : Handling Text Data : Analysis of Text Data – Frequency & Plots Video
  2. Lecture 53 : Selection of Sample : Simple Random Sampling Video
  3. Lecture 54 : Selection of Sample : Simple Random Sampling with R Video
  4. Lecture 55 : EDA with Multivariate Data : Sum and Mean Vectors Video
  5. Lecture 56 : EDA with Multivariate Data : Covariance and Correlation Matrices Video

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Kanpur
Department
Computer Science and Engineering
Teacher
Prof. Shalabh
Level
Undergraduate
Language
English
Subjects
Computer science, Engineering
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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