Hi sir, your teaching is so nice and understandable. Thank you so for being here. Also, please provide some information about AI and ML and also Data science.
Introduction of the R language, numeric, arithmetic, assignment, and vectors, Matrices and Arrays, Non-numeric Values, Lists and Data Frames, Special Values, Classes, and Coercion ,Basic plotting.. Unit 2 Reading and writing files, Programming, Calling Functions, Conditions and Loops; stand-alone statement with illustrations in exercise 10.1,stacking statements, coding loops. Writing Functions, Exceptions, Timings, and Visibility. Unit 3 Statistics And Probability, basic data visualisation, probability, common probability distributions: common probability mass functions, bernoulli, binomial, poisson distributions, common probability density functions, uniform, normal, student's t-distribution. Unit 4 Statistical testing and modelling, sampling distributions, hypothesis testing, components of hypothesis test, testing means, testing proportions, testing categorical variables, errors and power, Analysis of variance. Unit 5 Simple linear regression, multiple linear regression, linear model selection and diagnostics. Advanced graphics: plot customization, plotting regions and margins, point and click coordinate interaction, customizing traditional R plots, specialized text and label notation. Defining colors and plotting in higher dimensions, representing and using color, 3D scatter plots. Please please do this sir.........
Hi sir, your teaching is so nice and understandable. Thank you so for being here. Also, please provide some information about AI and ML and also Data science.
Very good sir
Introduction of the R language, numeric, arithmetic, assignment, and vectors, Matrices and Arrays, Non-numeric Values, Lists and Data Frames, Special Values, Classes, and Coercion ,Basic plotting..
Unit 2
Reading and writing files, Programming, Calling Functions, Conditions and Loops; stand-alone statement with illustrations in exercise 10.1,stacking statements, coding loops. Writing Functions, Exceptions, Timings, and Visibility.
Unit 3
Statistics And Probability, basic data visualisation, probability, common probability distributions: common probability mass functions, bernoulli, binomial, poisson distributions, common probability density functions, uniform, normal, student's t-distribution.
Unit 4
Statistical testing and modelling, sampling distributions, hypothesis testing, components of
hypothesis test, testing means, testing proportions, testing categorical variables, errors and power, Analysis of variance.
Unit 5
Simple linear regression, multiple linear regression, linear model selection and diagnostics.
Advanced graphics: plot customization, plotting regions and margins, point and click
coordinate interaction, customizing traditional R plots, specialized text and label notation.
Defining colors and plotting in higher dimensions, representing and using color, 3D scatter plots.
Please please do this sir.........