ICAR-IASRI MSc and PhD Programming for Statistics & Data (R and Python): practice questions

ICAR-IASRI MSc and PhD (Agricultural Statistics, Computer Application, Bioinformatics) · India · ICAR-Indian Agricultural Statistics Research Institute with the IARI Graduate School

Original practice questions written to the published syllabus · not past papers

10worked here, free

31written to this exam in this subject

8syllabus units

What this subject covers

Writing correct, readable programs for data work: R and Python as the working languages, with the control structures, functions, data frames, vectorisation and debugging habits that later computing subjects assume. C and SAS are covered where agricultural universities still teach them.

In the exams: GATE DA 'Programming, Data Structures and Algorithms' (heavy: Python named); AICE-JRF Computer Application Unit 2 programming (heavy); AIEEA-PG Group 07 computer programming (present)

Algorithms, flowcharts and pseudocode
R: vectors, data frames, factors and lists
R: functions, control flow and vectorisation
Python: core types, NumPy arrays and pandas data frames
Reading, cleaning and reshaping data
Graphics in R (base and ggplot2) and Python (matplotlib)
Writing functions and simple packages
Debugging, testing and code style
SAS DATA and PROC steps for agricultural analyses
Introduction to C: data types, arrays, pointers and file handling

Where the 31 questions fall

How our questions for ICAR-IASRI MSc and PhD spread across the units of Programming for Statistics & Data (R and Python). Difficulty: 13 easy, 18 medium, 0 hard.

R: vectors, data frames, factors and lists	7
R: functions, control flow and vectorisation	6
Graphics in R (base and ggplot2) and Python (matplotlib)	4
Writing functions and simple packages	4
Algorithms, flowcharts and pseudocode	3
Reading, cleaning and reshaping data	3
Debugging, testing and code style	3
Python: core types, NumPy arrays and pandas data frames	1

10 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · R: vectors, data frames, factors and lists · medium

For a list lst in R, lst[1] and lst[[1]] return respectively:

The element itself, and then a list containing it
The same object in both cases
A list of length one, and the element itself
An error, and the element

Answer and working

C. A list of length one, and the element itself

Single brackets subset the list; double brackets extract the element.

Further reading: Wickham and Grolemund, R for Data Science; McKinney, Python for Data Analysis (2022); Kernighan and Ritchie, The C Programming Language (1988); Delwiche and Slaughter, The Little SAS Book (2019)

2 · R: functions, control flow and vectorisation · medium

Why is seq_along(x) preferred to 1:length(x) in R loops?

seq_along(x) is always much faster in every case
1:length(x) is not valid syntax
seq_along(x) skips missing values
1:length(x) gives c(1, 0) when x is empty

Answer and working

D. 1:length(x) gives c(1, 0) when x is empty

With an empty x, 1:0 runs the loop twice with invalid indices; seq_along gives an empty sequence.

3 · R: functions, control flow and vectorisation · medium

R's lexical scoping means that a function looks up a free variable:

In the environment where it is called
Only among its arguments
Where the function was defined
Only in the global environment

Answer and working

C. Where the function was defined

Lookup follows the defining environment, then its parents.

4 · Reading, cleaning and reshaping data · medium

Which join keeps only rows whose keys appear in both tables?

Left join
Full join
Right join
Inner join

Answer and working

D. Inner join

Left and right joins keep all rows of one table; full keeps all of both.

5 · Graphics in R (base and ggplot2) and Python (matplotlib) · easy

Which ggplot2 function splits a plot into panels by a variable?

facet_wrap
geom_smooth
scale_colour
coord_flip

Answer and working

A. facet_wrap

Facets create small multiples.

6 · Graphics in R (base and ggplot2) and Python (matplotlib) · medium

The grammar of graphics that ggplot2 implements was set out by:

Tukey
Fisher
Knuth
Wilkinson

Answer and working

D. Wilkinson

Leland Wilkinson's The Grammar of Graphics.

7 · Graphics in R (base and ggplot2) and Python (matplotlib) · medium

A scatter-plot matrix of several variables in base R is drawn with:

histogram()
barplot()
boxplot()
pairs()

Answer and working

D. pairs()

pairs plots every pair of variables.

8 · Writing functions and simple packages · medium

Declaring package dependencies and versions for a project mainly prevents:

Viruses and malware on the shared computer
Data entry errors
Breakage when shared libraries change
Slow plotting

Answer and working

C. Breakage when shared libraries change

Pinned versions and project environments keep analyses reproducible.

9 · Writing functions and simple packages · easy

A well-designed function should:

Print every intermediate value
Use as many global variables as possible
Be as long as possible
Return values, not change globals

Answer and working

D. Return values, not change globals

Pure, focused functions are easier to test and reuse.

10 · Debugging, testing and code style · medium

Which is a testing framework for R?

ggplot2
testthat
tidyr
Rcpp

Answer and working

B. testthat

pytest is the common Python framework.

Ten here, 31 in the app. The Laisha app has every practice question we have written to ICAR-IASRI MSc and PhD in this subject, marked as you go, with timed papers, a jump-to-unanswered list and a certificate when you pass at 70 per cent.

Free for ten days, then one subscription of US$10 a month. We would rather say so here than have you find it later.

Practise the full set in Laisha →