1. Variables and Types of Data

2.   Qualitative variables are variables that can be placed into distinct categories, according to some characteristic or attribute. Example: gender  Quantitative variables are numerical and can be ordered or ranked. Example: age Variables

3.  1.Marital status of teachers in the school 2.Time it takes to complete a test 3.Weight of tiger cubs at birth in a zoo 4.Colors of cars for sale at a dealership 5.SAT score 6.Ounces of soda in a cup Classify each variable as Quantitative or Qualitative

4.  Quantitative variables can be classified into two groups: discrete and continuous.  Discrete variables assume values that can be counted. Example: number of students in a class  Continuous variables can assume an infinite number of values between any two specific values. They are obtained by measuring. Often including fractions and decimals. Example: temperature Discrete vs. Continuous

5.  VariableRecorded ValueBoundaries Length15 cm 14.5 – 15.5 cm Temperature86 degrees Fahrenheit85.5 – 86.5° F Time0.43 seconds0.425 – 0.435 sec Mass1.6 grams1.55 – 1.65 g Continuous Variables Boundaries

6.   Measurement scales classify variables by how they are categorized, counted, or measured. Example: area of residence, height  The four common types of scales that are used are: nominal, ordinal, interval, and ratio Measurement Scales

7.   Classifies data into mutually exclusive (nonoverlapping) categories in which no order or ranking can be imposed on the data Examples:  Gender  Zip code  Political party  Religion  Marital status Nominal Level of Measurement

8.   Classifies data into categories that can be ranked, however, precise differences between the ranks do not exist Examples:  First, second, third place  Superior, average, or poor  Small, medium, or large Ordinal level of Measurement

9.   Ranks data, and precise differences between units of measure do exist; however, there is no meaningful zero  Different from ordinal because precise differences do exist between units Examples:  IQ (no zero because it does not measure people without intelligence)  Temperature (no zero because temperature exists even at 0°) Interval level of Measurement

10.   Possesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist when the same variable is measured on two different members of the population Examples:  Height  Weight  Area Ratio level of Measurement

11.  There is not complete agreement among statisticians about classification of data. And data can be altered so that they fit into different categories. Examples:  Income: low, medium high (ordinal) or $100,00, $45, 000, etc. (ratio)  Grade: A, B, C, D, F (ordinal) or 100, 90, 80, etc. (interval) Agreement?

12.  Classify each variable as nominal, ordinal, interval, or ratio Judging a costume contest (1 st, 2 nd, 3 rd ) TimeAge Eye ColorSAT scoreNationality GenderGrade (A, B, C, D, F)Temperature SalaryIQRating Scale (poor, fair, good, excellent) College MajorArea CodeHeight

13.   Pg. 9 #1-7 Try it!