Skip to content

B.Tech 3rd Year Statistics with R Programming Study Materials BOOK PDF | Download B.Tech 3rd Year Statistics with R Programming Study Materials BOOK PDF

Here, we have provided the links containing the study materials, which will help you study and prepare for your B.Tech 3rdStatistics with R Programming 2020 edition examinations. Referring to the connections we’ve provided below and the links containing the study materials in PDF format, and the list of recommended books that we’ve provided below, you will be able to ace your examinations. We have also provided you with further details that will allow you to do well in your exams and learn more. These study materials help you understand the concepts and everything quickly and creates a better space for you to work on. These study materials give you the best resources to study from. 

Statistics with R Programming

Here, we are talking about using the program language R for statistical programming, computation, graphics and modeling, writing functions, and efficiently using R.

Download Statistics with R Programming

introduction to r statisticsDownload
introduction to r programmingDownload
Statistics with R Programming notes pdf Study materialDownload
Statistics with R Programming Question PaperDownload

Recommended Books

  • The Art of R Programming, Norman Matloff, Cengage Learning
  • R for Everyone, Lander, Pearson
  • Siegel, S. (1956), Nonparametric Statistics for the Behavioral Sciences, McGraw-Hill International, Auckland.
  • R Cookbook, PaulTeetor, Oreilly.
  • R in Action, Rob Kabacoff, Manning
  • Venables, W. N., and Ripley, B. D. (2000), S Programming, Springer-Verlag, New York.
  • Venables, W. N., and Ripley, B. D. (2002), Modern Applied Statistics with S, 4th ed., Springer-Verlag, New York.
  • Weisberg, S. (1985), Applied Linear Regression, 2nd ed., John Wiley & Sons, New York.
  • Zar, J. H. (1999), Biostatistical Analysis, Prentice Hall, Englewood Cliffs, NJ



Introduction, How to run R, R Sessions, and Functions, Basic Math, Variables, Data Types, Vectors, Conclusion, Advanced Data Structures, Data Frames, Lists, Matrices, Arrays, Classes.


R Programming Structures, Control Statements, Loops, – Looping Over Nonvector Sets,- If-Else, Arithmetic, and Boolean Operators and values, Default Values for Argument, Return Values, Deciding Whether to explicitly call return- Returning Complex Objects, Functions are Objective, No Pointers in R, Recursion, A Quicksort Implementation-Extended Extended Example: A Binary Search Tree.


Doing Math and Simulation in R, Math Function, Extended Example Calculating Probability- Cumulative Sums and Products-Minima and Maxima- Calculus, Functions Fir Statistical Distribution, Sorting, Linear Algebra Operation on Vectors and Matrices, Extended Example: Vector cross Product- Extended Example: Finding Stationary Distribution of Markov Chains, Set Operation, Input /out put, Accessing the Keyboard and Monitor, Reading and writer Files,


Graphics, Creating Graphs, The Workhorse of R Base Graphics, the plot() Function – Customizing Graphs, Saving Graphs to Files.


Probability Distributions, Normal Distribution- Binomial Distribution- Poisson Distributions Other Distribution, Basic Statistics, Correlation and Covariance, T-Tests,-ANOVA.


Linear Models, Simple Linear Regression, -Multiple Regression Generalized Linear Models, Logistic Regression, – Poisson Regression- other Generalized Linear Models-Survival Analysis, Nonlinear Models, Splines- Decision- Random Forests,

Important Questions

  • Explain about Variables, Constants and Data Types in R Programming
  • How to create, name, access, merging, and manipulate list elements? Explain with examples.
  •  Write about Arithmetic and Boolean operators in R programming?
  •  How to create user-defined function in R? How to define default values in R? Write syntax and examples?
  •  Explain functions for accessing the keyboard and monitor, Reading and writing files
  •  Write an R function to find sample covariance.
  • Write about the following functions with example
    a)points() b) legend() c)text() d) locator()
  •  Describe R functions for Reading a Matrix or Data Frame From a File
  • Fit a poisson distribution to the following data
    x 0,1,2,3,4,5
    f 3,9,12,27,4,1
    Also, test the adequacy of the model
  •  Calculate the coefficient of correlation to the following data
    X 10 12 18 24 23 27
    Y 13 18 12 25 30 10

Leave a Reply

Your email address will not be published. Required fields are marked *