1. Statistics Introduction Part 2

2. Statistics Warm-up Classify the following as a) impossible, b) possible, but very unlikely, or c) possible and likely: The Patriots will beat the Miami Doplhins 120 – 98 this Monday. Thanksgiving will fall on a Monday next year. When each of you turn on your graphing calculator, they will all operate successfully.

3. Statistics Agenda Warm-up Homework Review Objective Distinguish between qualitative data and quantitative data Classify data with respect to the four levels of measurement Summary Homework

4. Types of Data Qualitative Data Consists of attributes, labels, or nonnumerical entries. MajorPlace of birth Eye color

5. Types of Data Quantitative data Numerical measurements or counts. AgeWeight of a letterTemperature

6. Example: Classifying Data by Type The base prices of several vehicles are shown in the table. Which data are qualitative data and which are quantitative data? (Source Ford Motor Company)

7. Solution: Classifying Data by Type Quantitative Data (Base prices of vehicles models are numerical entries) Qualitative Data (Names of vehicle models are nonnumerical entries)

8. Distinguish between Discrete and Continuous Variables

9. A discrete variable is a quantitative variable that either has a finite number of possible values or a countable number of possible values. The term “countable” means the values result from counting such as 0, 1, 2, 3, and so on. A continuous variable is a quantitative variable that has an infinite number of possible values it can take on and can be measured to any desired level of accuracy.

10. Researcher Elisabeth Kvaavik and others studied factors that affect the eating habits of adults in their mid-thirties. (Source: Kvaavik E, et. al. Psychological explanatorys of eating habits among adults in their mid-30’s (2005) International Journal of Behavioral Nutrition and Physical Activity (2)9.) Classify each of the following quantitative variables considered in the study as discrete or continuous. a.Number of children b.Household income in the previous year c.Daily intake of whole grains (measured in grams per day) EXAMPLE Distinguishing between Qualitative and Quantitative Variables Discrete Continuous

11. Levels of Measurement Nominal level of measurement Qualitative data only Categorized using names, labels, or qualities No mathematical computations can be made Ordinal level of measurement Qualitative or quantitative data Data can be arranged in order Differences between data entries is not meaningful

12. Example: Classifying Data by Level Two data sets are shown. Which data set consists of data at the nominal level? Which data set consists of data at the ordinal level? (Source: Nielsen Media Research)

13. Solution: Classifying Data by Level Ordinal level (lists the rank of five TV programs. Data can be ordered. Difference between ranks is not meaningful.) Nominal level (lists the call letters of each network affiliate. Call letters are names of network affiliates.)

14. Levels of Measurement Interval level of measurement Quantitative data Data can ordered Differences between data entries is meaningful Zero represents a position on a scale (not an inherent zero – zero does not imply “none”)

15. Levels of Measurement Ratio level of measurement Similar to interval level Zero entry is an inherent zero (implies “none”) A ratio of two data values can be formed One data value can be expressed as a multiple of another

16. Example: Classifying Data by Level Two data sets are shown. Which data set consists of data at the interval level? Which data set consists of data at the ratio level? (Source: Major League Baseball) New York Yankees’ World Series Victories (years) 1923,1927,1928,1936,1937, 1938, 1939, 1941, 1943, 1947, 1949, 1950, 1951, 1952, 1953, 1956, 1958, 1961, 1962, 1977, 1978, 1996, 1999, 2000, 2009 2006 American Leagues Home Run Totals (by team) Baltimore 164 Boston 192 Chicago 236 Cleveland 196 Detroit 203 Kansas City 124 Minnesota 143 New York 210 Oakland 175 Seattle 172 Tampa bay 190 Texas 183 Toronto 199

17. Solution: Classifying Data by Level Interval level (Quantitative data. Can find a difference between two dates, but a ratio does not make sense.) Ratio level (Can find differences and write ratios.) New York Yankees’ World Series Victories (years) 1923,1927,1928,1936,1937, 1938, 1939, 1941, 1943, 1947, 1949, 1950, 1951, 1952, 1953, 1956, 1958, 1961, 1962, 1977, 1978, 1996, 1999, 2000, 2009 2006 American Leagues Home Run Totals (by team) Baltimore 164 Boston 192 Chicago 236 Cleveland 196 Detroit 203 Kansas City 124 Minnesota 143 New York 210 Oakland 175 Seattle 172 Tampa bay 190 Texas 183 Toronto 199

18. Summary of Four Levels of Measurement Level of Measurement Put data in categories Arrange data in order Subtract data values Determine if one data value is a multiple of another NominalYesNo OrdinalYes No IntervalYes No RatioYes

19. Summary Distinguished between qualitative data and quantitative data Classified data with respect to the four levels of measurement

20. Homework Pg 13-14 # 1-21 odd