Probability and Statistics Chapter 1 Notes

Probability and Statistics Chapter 1 Notes II. Section 1-2 A. Types of Data 1. Qualitative Data a. Attributes, labels or non-numerical entries. 2. Quantitative Data a. Numerical measurements or counts. B. Levels of Measurement 1. Nominal Data a. Consists of names, categories, qualities, or labels. Example: type of car you drive. b. Can put data into categories, but we are unable to determine if one piece of data is better or higher than another. c. When numbers are used as labels, such as on an athletic jersey, they are classified as nominal data.

Probability and Statistics Chapter 1 Notes II. Section 1-2 2. Ordinal Data a. Designations or numerical rankings which can be arranged in ascending or descending order. 1) TV ratings for #1 show, #2 show, etc. b. We can compare rankings as to which is higher, however it does not make sense to subtract one rank value from another. 1) Differences in rankings are not meaningful computations.

Probability and Statistics Chapter 1 Notes II. Section 1-2 3. Interval Data a. Can be subtracted to find the difference between two values, put in order, and put into categories. b. Data is numerical; 0 can be used to indicate a position in time or space, however, the zero at this level does not correspond to “none” of the specific variable being measured. 1) The position on the thermometer of zero degrees does not indicate that is absolutely no heat present. c. Differences between data values are meaningful but it does not make sense to compare one data value as being twice (or any multiple of) another. 1) The two most common uses are for elapsed time and temperature.

Probability and Statistics Chapter 1 Notes II. Section 1-2 4. Ratio Data a. The highest level of measurement. 1) The number of gallons of gasoline you put into your car today. b. There is a zero on this scale which is interpreted as “none” of the variable in question. 1) It is possible to put zero gallons of gas into your tank today. 2) This is called an “inherent” zero. c. It is meaningful to say one measure is two times, or three times, as much as another. 1) You may have put twice as much gas in your car today than you did last week.

Probability and Statistics Chapter 1 Notes II. Section 1-2 5. How to tell Interval data from Ratio data. a. Does the expression “twice as much” have any meaning in the context of the data? 1) $2 is twice as much as $1, so these data points are at the ratio level. 2) A temperature of 2 degrees is NOT twice as warm as 1 degree is, so these data points are at the interval level.

Assignment: Classwork: Pages 8-10, #1-38 ALL Classwork: Page 15, #1-12 ALL Homework: Pages 15-16 #13-24 ALL