There are four levels of measurement for data: nominal, ordinal, interval, and ratio. Nominal data involves categorizing subjects into groups without order. Ordinal data ranks categories in a low-to-high order. Interval data involves distances of equal size between numbers on the scale, but without a true zero point. Ratio data contains all interval properties and has a true zero point, allowing for calculations like percentages.

1. Levels of Measurement of Data Measurement , it is assigning a numerical value to a variable. For example, the reading of a thermometer is 35ºC, or when examining bulbs, 3 are defective. Nominal Data (Classificatory Scale) is the weakest level of measurement where numbers or symbols are used simply for categorizing subjects into different groups. Examples: Gender ->M= Male , F = Female Marital Status -> 1 = Single , 2= Married , 3= Widowed , 4 = Separated

2. b. Ordinal Data (Ranking Scale ) contains properties of the nominal level and in addition, the numbers assigned to categories of any variable may be ranked or ordered in some low- to high manner. This type of data, numbers represents “greater than” or “less than” measurements. Examples: -Year Level -> 1= 1st y r, 2= 2nd yr ,3 = 3rd yr, 4 = 4th yr - Ratings -> 1= Poor , 2= Fair, 3= Good , 4 = Excellent

3. Interval Data has the properties of the ordinal and in addition, the distances between any two numbers on the scale are known sizes, interval scale must have a common and constant unit of measurement ( unit of measurement is arbitrary and there is NO ZERO point). Examples: -IQ Level -Temperature d. Ratio contains all the properties of the interval level and in addition, has a TRUE ZERO point Examples: -Scores in a certain test -Age ( in years ) -Election vote -Weight, height, length, area, volume, density, velocity, money, etc.