DIFFERENT TYPES OF DATAA variable is any characteristic observed in a study. The data values that we observe for a variable are called observations. A variable can be categorical and quantitative.Categorical variables are variables that belong to a distinct set of categories. A categorical variable can be numerical, because some variables do not vary in quantity. (e.g: religion, favourite sport, bank account, area codes)Quantitative variables are variables that have numerical values and represent different magnitudes. (e.g: weight, height, hours spent watching TV every day)Key features to describe quantitative variables are the centre and the variability (spread) of the data (e.g: average amount of hours spent watching TV every day). Key feature to describe categorical variables is the relative number of observations in various categories. (e.g: the percentage of days in a year that it was sunny)Quantitative variables can be discrete and continuous. A quantitative variable is discrete if its possible values form a set of separate numbers, such as 0, 1, 2, 3 (e.g: the number of pets in a household). A quantitative variable is continuous if its possible values form an interval, such as 0.16, 0,13, 2,32 (e.g: weight: 68,3 kg).The distribution of a variable describes how the observations fall (are distributed) across the range of possible values. The modal category is the category with the largest frequency.A frequency table is a listing of possible values for a variable, together with the number of observations for each value. CategoryABCFrequency17239Proportion0.3470.4690.184Percentage34.7%46.9%18.4%an example of a frequency tableThe proportion of observations falling in a certain category is the number of observations in that category divided by the total number of observations. The percentage is the proportion multiplied by 100. Proportions and percentages are also called...