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Course11110576220 lectures

Basics of Nonparametric Tests with Applications by R

Prof. Saran Ishika Maiti · Visva Bharati University, Santiniketan

Start with lecture 1 At NPTEL

About

Nonparametric inference is essential when either the usual Gaussian assumption would fall short or sample size is too small to undergo with the Gaussian assumption. Till date most of the data analysis adheres to the test constructed on Gaussian assumption. This course will enable the students to understand why and when nonparametric tests are more pertinent. The theme of the course is not only focusing towards theory but also emphasizing more to data analysis.

Although this course is designed for a 4-week (10 hr) course the learning items under it covers almost all basic nonparametric tests valid for potential Analysis. Students will learn one sample location and scale test, two sample tests, K-sample tests like nonparametric ANOVA and goodness of fit tests, garnered with evoking examples. The course will benefit not only the undergraduate students of Statistics but also guide the researchers from different disciplines like biological sciences, social sciences, agricultural sciences.

Intended audience: Undergraduate students in Statistics/Data Sciences, Researchers from BioSciences, Agriculture Sciences, Social Sciences etc.

Prerequisites: A minor course in Introductory Statistical Inference

Lectures

Week 1

  1. Lecture -1 : Need of Nonparametric Inference YouTube
  2. Lecture -2 : Rank and Permutation YouTube
  3. Lecture -3 : Spearman Rank Correlation YouTube
  4. Lecture -4 : Kendall’s Rank Correlation YouTube
  5. Lecture -5 : Linear Rank Statistics (Part B) YouTube

Week 2

  1. Lecture -6 : Sign Test YouTube
  2. Lecture -7 : Problem Solving on Wilcoxon signed rank test YouTube
  3. Lecture -8 : Kendall’s Rank Correlation YouTube
  4. Lecture -9 : Paired Sample Wicoxon signed rank test YouTube
  5. Lecture -10 : McNemar’s Test YouTube

Week 3

  1. Lecture -11 : General discussion on two sample test & Mann Whitney Test YouTube
  2. Lecture -12 : Tie cases, (Wilcoxon)Mann Whitney Statistic & Problem Solving by R YouTube
  3. Lecture -13 : Median Test and Mood’s Tests for dispersion YouTube
  4. Lecture -14 : Wald Wolfowitz Run Test YouTube
  5. Lecture -15 : Extension to two sample proble YouTube
  6. Lecture -16 : Friedman Test (Two -way Nonparametric ANOVA) YouTube

Week 4

  1. Lecture -17 : Few Forewords and Pearson Goodness of fit Test YouTube
  2. Lecture -18 : One Sample Kolmogorov Smirnov Test YouTube
  3. Lecture -19 : Two sample Kolmogorov Smirnov Test YouTube
  4. Lecture -20 : Few Other Goodness of Fit Tests YouTube

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
Visva Bharati University, Santiniketan
Department
Mathematics
Teacher
Prof. Saran Ishika Maiti
Level
Undergraduate
Language
English
Subjects
Mathematics
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. Coordinated by IIT Kharagpur.
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