The word "data" is a general purpose word denoting a collection of measurements. There is a debate raging amongs statisticians about whether the word should be singular or plural.^[1,p.2][8] For the purposes of this website "data" is treated as a singular non-countable noun (like "butter"), while "data points" are countable and plural (like "packs of butter") that refer to individual instances of data. A data set is a well-structured set of data points. Data points can be of several data types, such as numbers, or text, or date-times. When data on similar objects is collected, the data points are bundled into a variable.^[9] A variable is a characteristic that's being counted, measured or categorised, e.g. age, number of pets, favourite color etc.^[1,p.16] The measurements, number (count) or category (group) associated with data points are called values of the variable.^[9] A statistic is a number that summarises or describes some characteristic (i.e. variable) of a data set.^[1,p.71]

Qualitative (Categorical) Data

Qualitative data represent characteristics, e.g. marital status, hometown, favourite color etc. Qualitative data tends to fall into categories naturally, and is also known as categorical data. Qualitative data can be coded by numerical values, but meaningful arithmetical operations cannot be performed on those numbers. Sometimes numerical data, like age, that would normally be considered quantitative data, is broken down into categories, making it a qualitative variable. Qualitative data often comes from surveys, but it can be collected in experiments as well.^{[1,pp.50,72-73]}

If the data is categorical, it is typically summarised using frequency or relative frequency. Frequency is the number of data points in each category. Relative frequency is the percentage of the category within the data set.^[1,p.15] Rate is an amount-per-unit measure of event frequency that is obtained by converting each number to a percent by dividing it by the total. Rates are usually better than absolute values because rates allow for fair comparisons when the totals are different.^[1,p.39]

Some of the basic graphs used for categorical data include pie chart and bar graphs .^[1,p.16]

Quantitative (Numerical) Data

Quantitative data are measures of values or counts that are expressed as numbers.^[3] Quantitative data can be further broken down into two types:^[1,p.50]

• Discrete data- represents separate, countable items that take on possible values that can be listed. The list of values may be finite or infinite.
• Continuous data- represents measurements with possible values that can not be listed, and can only be described using intervals on the real number line.

Some of the measures of quantitative data include:^[1,p.15]

• Measures of center- mean and median
• Measures of spread- standard deviation and percentiles
• Measures of relationship