Introduction to R and RStudio

False (B)

liters

<p>tibble</p> Signup and view all the answers

<p>displ = Engine size, in liters hwy = Car's fuel efficiency on the highway, in miles per gallon model = Car’s model class = Car’s class</p> Signup and view all the answers

<p>A programming language and environment for statistical computing, analysis, and graphics (B)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>RStudio is an integrated development environment (IDE) for R programming.</p> Signup and view all the answers

<p>RMarkdown</p> Signup and view all the answers

<p>It is the fastest programming language available (C)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>Operators = Symbols used to perform calculations and comparisons Control Flow = Mechanisms that dictate the order in which code is executed Data Wrangling = The process of cleaning and transforming data Data Visualization = Graphical representation of data</p> Signup and view all the answers

<p>R is free, open-source and available on every major platform.</p> Signup and view all the answers

<p>To answer questions while accounting for variability (A)</p> Signup and view all the answers

<p>hash</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>Monte Carlo simulation (A)</p> Signup and view all the answers

<p>c()</p> Signup and view all the answers

<p>Hypothesis testing = A method to answer questions while accounting for variability Monte Carlo Simulation = A numerical method to estimate probabilities Comment in R Code = Ignored by the R interpreter <code>c()</code> function = Combines values into a vector</p> Signup and view all the answers

<p>To share your findings with others (D)</p> Signup and view all the answers

<p>True (A)</p> Signup and view all the answers

<p>hwy (D)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>cut</p> Signup and view all the answers

<p>sugar content</p> Signup and view all the answers

<p>Categorical = Bar Chart Continuous = Scatterplot Time Series = Line Chart Distribution = Histogram</p> Signup and view all the answers

<p>class (B)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>sugar content</p> Signup and view all the answers

<p>date</p> Signup and view all the answers

<p>Scatterplot = Relationship between two continuous variables Bar Chart = Comparison between categorical values Line Chart = Showing trends over time Boxplot = Distribution of a variable across groups</p> Signup and view all the answers

<p>Relationship between 'displ' &amp; 'hwy' (B)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>numeric</p> Signup and view all the answers

<p>class</p> Signup and view all the answers

<p>Scatterplot = Two Numerical Variables Boxplot = One Numerical and One Categorical Variable Line Chart = One Numerical and Time variable Bar Chart = One Numerical and One Categorical Variable</p> Signup and view all the answers

R is a free, open-source programming language designed for statistical computing, analysis, and graphics. It's widely used in data science, offering a vast library of packages and tools.

RStudio is an integrated development environment (IDE) that enhances working with R. It provides a user-friendly interface for writing, running, and visualizing R code.

R's open-source nature allows anyone to access and use it freely. It's available on all major operating systems.

R excels in data manipulation, offering powerful tools for cleaning, restructuring, and transforming data into a usable format.

R provides a vast collection of packages that extend its capabilities. These packages offer specialized functions for various tasks like statistical modeling, machine learning, and visualization.

R's ability to connect to languages like C, Fortran, and C++ allows for faster processing and optimization for computationally demanding tasks.

R excels at creating informative and visually appealing graphs. It can help to illustrate patterns and insights hidden within data.

RMarkdown allows you to combine code, text, and output into a single document, facilitating the creation of reports, presentations, and even interactive web applications.

A car's engine size, measured in liters.

A car's fuel efficiency on the highway, measured in miles per gallon (mpg).

A higher 'hwy' value means the car is more fuel-efficient, using less fuel to travel the same distance.

mpg dataset contains information about cars, and variables like 'displ' and 'hwy' can be used to analyze and compare car performance.

The 'ggplot2' package allows you to create more attractive and informative plots compared to basic plotting functions.

A scatterplot visually represents the relationship between two continuous variables. Each point on the plot corresponds to a data point, with its horizontal position indicating the value of one variable and its vertical position indicating the value of the other. It helps visualize the trend, correlation, and potential outliers in the data.

In a scatterplot, color-coding points by a third variable, called a "class variable", helps you identify patterns within the data. You can see how different categories cluster based on the relationship of the two primary variables.

A line chart, also known as a time-series plot, displays the relationship between a variable and time. It's used to show trends, patterns, and changes over a period, often used for data like unemployment rates over years.

A bar chart is used to compare different categories of data. It uses bars of different lengths, where the height of each bar represents the value of the category it represents. This helps visualize magnitudes and differences between groups.

A boxplot summarizes the distribution of a continuous variable using five key points: minimum, first quartile, median, third quartile, and maximum. It helps understand the central tendency, spread, and potential outliers of the data.

A histogram is a bar chart that displays the distribution of a continuous variable. The height of each bar represents the frequency or density of data points within a specific range of values, providing a visualization of the data's shape and how values are spread.

A warning that appears when the after_stat() function is called more than once within an 8-hour window.

It's a set of tools for answering questions about the data.

It's a technique where you simulate random events to estimate probabilities, expectations, and integrals.

Methods like optim help in maximizing a multi-parameter likelihood function.

It combines statistical methods with computer science techniques to extract insights from data.

It involves presenting your findings to others in a clear and concise way.

It's a method to add comments to R code.

It's a function in R used to combine different values together into a vector.