Introduction to Data Science Using R Runestone Version 1

In R, as in other programs, a vector is a list of elements/things that are all of the same kind, or what R refers to as a mode. For example, a vector of mode "numeric" would contain only numbers.

Statisticians, database experts and others like to work with rectangular datasets where the rows are cases or instances and the columns are variables or attributes.

In R, one of the typical ways of storing these rectangular structures is in an object known as a dataframe. Technically speaking a dataframe is a list of vectors where each vector has the exact same number of elements as the others (making a nice rectangle).

In R, the data.frame() function organizes a set of vectors into a dataframe. A dataframe is a conventional, rectangular shaped data object where each column is a vector of uniform mode and having the same number of elements as the other columns in the dataframe. Data is copied from the original source vectors into new storage space. The variables/columns of the dataframe can be accessed using "$" to connect the name of the dataframe to the name of the variable/column.

The str() and summary() functions can be used to reveal the structure and contents of a dataframe (as well as of other data objects stored by R). The str() function shows the structure of a data object, while summary() provides numerical summaries of numeric variables and overviews of non-numeric variables.

A factor is a labeling system often used to organize groups of cases or observations. In R, as well as in many other software programs, a factor is represented internally with a numeric ID number, but factors also typically have labels like "Male" and "Female" or "Experiment" and "Control." Factors always have "levels," and these are the different groups that the factor signifies. For example, if a factor variable called Gender codes all cases as either "Male" or "Female" or "Other" then that factor has exactly three levels.

Quartiles are a division of a sorted vector into four evenly sized groups. The first quartile contains the lowest-valued elements, for example the lightest weights, whereas the fourth quartile contains the highest-valued items. Because there are four groups, there are three dividing lines that separate them. The middle dividing line that splits the vector exactly in half is the median. The term "first quartile" often refers to the dividing line to the left of the median that splits up the lower two quarters and the value of the first quartile is the value of the element of the vector that sits right at that dividing line. Third quartile is the same idea, but to the right of the median and splitting up the two higher quarters.

Min and max are often used as abbreviations for minimum and maximum and these are the terms used for the highest and lowest values in a vector. Bonus: The "range" of a set of numbers is the maximum minus the minimum.

The mean is the same thing that most people think of as the average. Bonus: The mean and the median are both measures of what statisticians call "central tendency."