Types of Data Four types of data Alphabetical

Types of Data

Four types of data • Alphabetical / Categorical / Nominal data: – Information falls only in certain categories, not inbetween categories – No inferences possible between groups except that one group may contain more / less observations than the other – Only reporting frequencies, percentages and mode makes sense (descriptive statistics) – Chi Square measure of Association (inferential Statistics) – Examples: gender, age groups, income groups, etc.

Four types of data • Rank order data: – Ranked according to some logic, e. g. preference, etc. – Again an in-between rank does not make sense. – Difference between say rank 1 and 2 need not necessarily be of the same magnitude as the difference between rank 3 and 4. – Only reporting frequencies, percentages and mode makes sense (descriptive statistics); Spearman Rho coefficient of correlation (Inferential statistics) – Examples: brand preferences, class rank on test, etc.

Four types of data • Interval Level – Numerical data in which the numbers denote the amount of presence / absence of a trait. – zero point does not necessarily mean complete absence of the trait – In-between numbers make sense – Magnitude of difference between numbers on the scale is constant. – All descriptive and inferential statistics possible – Examples: attitude, satisfaction, temperature, etc.

Four types of data • Ratio level data – Interval level data with a meaningful zero point meaning complete absence of the trait – Magnitude of the difference between numbers of the scale is constant AND the zero point denotes complete absence of the trait being measured. – All descriptive and inferential statistics possible – Examples: sales, profits, weight, height, etc.

Type of data? Age in years Recall order of brands Age groups Ad. costs Income groups Number of students in various classes Time Name Test grades SAT scores Number of players in a team Attitude to brand Number of students in WU Number of ads recalled Calories