Master in Data Science (SMS, TU) Statistical Computing with R Question Paper 2081 (Set pages 3-4; First Reassessment 2081) Nepal

Describe how can you import following types of data into the R software with simple examples/codes: a) a text file saved in the local computer b) a table embedded in any webpage c) json file with web API

Describe following data types in R with example R codes: a) Numeric and integer b) Categorical and factor c) Date and Date as well as time

Describe data mining in data science with focus and examples on: a) Descriptive mining b) Predictive mining c) Prescriptive mining

Explain how to work efficiently with "big data" in R software in relation to the: a) Subsetting with base R and dplyr packages b) ff, ffbase and ffbase2 packages c) data.table package

Explain social network analysis and describe its use in a real-life situation with: a) Nodes b) Links c) Attributes

Open the R or R studio software and do the followings with R script to produce HTML output: a) Define integers from 1 to 15 using three different coding approaches in R b) Define these five numbers: 1.1, 2.2, 3.3, 4.4 and 5.5 and save it as column vector N c) Add, subtract, multiply and divide vector R from vector N and interpret the results carefully d) Define a list using "This" "is" "my" "first" "programming" "in" "R" and save it as L

Import the "airquality" data as "aq" object in R studio and do as follows in R script for HTML output: a) Check the structure of the aq dataset and explain class of each variable b) Explain how to handle missing value of two variables of aq dataset c) Get the summary of all the variables and interpret them carefully d) Get summary statistics of "temp" variables by "Month" categories and interpret it carefully

Use the "aq" datafile in R studio and do as follows with R script to produce HTML outputs: a) Create bar plot of "Month" variable and interpret it carefully b) Create histogram of "Temp" variable and interpret it carefully c) Create line plot of "Temp" and "Day" variables and interpret it carefully d) Create scatterplot of "Ozone" and "Solar.R" variables and interpret it carefully

OR

Use the "mpg" dataset of tidyverse package and do as follows with R script to knit HTML output: a) Plot histogram of hwy variable and interpret it carefully b) Add a vertical abline at mean and $\pm 2$ standard deviation of hwy variable and interpret it carefully c) Locate mode of hwy variable graphically and interpret it carefully d) Locate median of hwy variable graphical and interpret it carefully

Do the following in R Studio with tidyverse package using R Script to knit HTML output: a) Define a tibble having country, year, cases and population variables with 20 random data each b) Transform the cases variable as log of cases (LnCase) and population variable as log of population (LnPop) c) Create scatterplots of 1. Cases and population, 2. LnCase and population, 3. Cases and LnPop and 4. LnCase and LnPop d) Show the four graphs in a single graph window

Load the "igraph" package in R studio and do the basic SNA as follows with R scripts for HTML output: a) Define g as graph object with (1,2) as its elements, plot it and interpret carefully b) Define g1 as graph object with ("S", "R", "R", "G", "G", "S", "S", "G", "A", "R") as its elements c) Plot g1 with node color as green, node size as 30, link color as red and link size as 5 and interpret it d) Get degree, closeness and betweenness of g1 and interpret them carefully

OR

Do as follows in R console and then to R Studio with R script to knit HTML outputs: a) Open R console and then go to Help and Manuals (in PDF) and open "An Introduction to R" file b) Save this file in the working directory and import this pdf file in R studio using "pdftools" package c) Perform pre-processing and create 'corpus' using "tm" package d) Find the most frequent terms and create histogram of the most frequent terms