Introduction to Statistical Thinking

Subsection 2.5.1 Glossary

Population

🔗

The collection, or set, of all individuals, objects, or measurements whose properties are being studied.

🔗

Sample

🔗

A portion of the population understudy. A sample is representative if it characterizes the population being studied.

🔗

Frequency

🔗

The number of times a value occurs in the data.

🔗

Relative Frequency

🔗

The ratio between the frequency and the size of data.

🔗

Cumulative Relative Frequency

🔗

The term applies to an ordered set of data values from smallest to largest. The cumulative relative frequency is the sum of the relative frequencies for all values that are less than or equal to the given value.

🔗

Data Frame

🔗

A tabular format for storing statistical data. Columns correspond to variables and rows correspond to observations.

🔗

Variable

🔗

A measurement that may be carried out over a collection of subjects. The outcome of the measurement may be numerical, which produces a quantitative variable; or it may be non-numeric, in which case a factor is produced.

🔗

Observation

🔗

The evaluation of a variable (or variables) for a given subject.

🔗

CSV Files

🔗

A digital format for storing data frames.

🔗

Factor

🔗

Qualitative data that is associated with categorization or the description of an attribute.

🔗

Quantitative

🔗

Data generated by numerical measurements.

🔗

Subsection 2.5.2 R functions introduced in this chapter

• data.frame() creates data frames, tightly coupled collections of variables which share many of the properties of matrices and of lists, used as the fundamental data structure by most of R’s modeling software.

  🔗
  🔗
• head() and tail() return the first or last parts of a data.frame.

  🔗
  🔗
• sum() and cumsum() returns the sum and cumulative sum of the values present in its arguments.

  🔗
  🔗
• read.csv(file) reads a file in table format and creates a data frame from it.

  🔗
  🔗

Subsection 2.5.3 Discuss in the forum