Manipulating dates and times is usually quite hard and confusing. When time zones come in, it gets even harder; but still, sometime one needs to process date-time objects in their code. Lubridate is one of a few great packages which makes things a bit easier. Answers to the exercises are available here. Please, do all […]

# Exercises (beginner)

## Graphics with Lattice: Exercise 1

In the exercises below, we will see features of the famous lattice graphics package. Please see the documentation before trying the exercises. Answers to the exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that […]

## Groups Comparison with ANOVA: Exercises (Part 1)

As we’re aware, the growth of data science has been increased recently, and successfully applied on research for decision making or creating baseline conditions. Statistical analysis, including data visualization, exploration, and modeling are three main important elements in data science. In this exercise, we’ll learn how to analyze response and explanatory variables of data that […]

## Tidy Data Reading: Exercises

Every analysis starts with data; and reading data from different sources into R can be very challenging. Multiple formats, multiple libraries, multiple interfaces, and so on. Fortunately, the authors of tidyverse created a number of packages to handle reading data in the most common formats in a simple, intuitive way. This exercise set will give you […]

## Functional Programming With Purrr: Exercises (Part 1)

One of R`s cool features is functional programming. It makes development much easier and the code you write shorter and less prone to errors. There are few tool kits for functional programming in R (with famous apply functions family among them). In this set of exercises, you will familiarize yourself with basic functions from the purrr […]

## Working With Factors: Exercises

Factor data type in R can be very painful to use, especially for beginners. Fortunately, like everything else, there are packages for working with factors. One of the packages is forcats by RStudio. In this set, you will have an opportunity to exercise it. Answers to the exercises are available here. Please, do all exercises […]

## Exercises With Raster Data (Part 1 and 2)

Geospatial data is becoming increasingly used to solve numerous ‘real-life’ problems (check out some examples here). In turn, R is becoming a powerful, open-source solution to handle this type of data, currently providing an exceptional range of functions and tools for GIS and Remote Sensing data analysis. In particular, raster data provides support for representing […]

## Introduction to Statistical Testing and Sampling: Exercises (Part 1)

For a majority of users, the primary use of R is for statistical testing and analysis. At the heart of this, within the frequentist world, lies hypothesis testing and distribution sampling. The skill in conducting this sort of work is being able to identify an appropriate distribution on which to model the question and test […]

## Predicting Housing Prices with Linear Regression Exercises

Regression techniques are a crucial skill in any data scientist or statisticians toolkit. It is even crucial for people who are unfamiliar with regression modeling. It is a nice way to introduce yourself to the topic through a simple linear model. A linear model is an explanation of how a continuous response variable behaves, dependent […]

## Basic Bayesian Inference for MCMC techniques : Exercises (Part 1)

This post aims to introduce you to the basics of Bayesian inference. The ultimate goal of this introductory set of exercises is to get you ready for Bayesian inference using Markov Chain Monte Carlo (MCMC). Little reminder The whole Bayesian paradigm is based on the Bayesian Theorem that we all know (right ?), generally formulated […]