1. 2-1 Ms. Kathryn Ball of AutoUSA wants to develop tables, charts, and graphs to show the typical selling price on various dealer lots. The table on the right reports only the price of the 80 vehicles sold last month at Whitner Autoplex.

2. 2-2 Frequency Distribution

3. 2-3 Frequency Distribution.

4. 2-4 Steps for Constructing a Frequency Distribution Array the data values in order by size from lowest to highest (or vice versa); Compute the range; Divide the range into a convenient number of class intervals of equal size; Count the number of observations in each class to determine the total frequency; and Display the class intervals with their frequencies.

5. 2-5 Constructing a Frequency Table - Example Step 1: Decide on the number of classes. A useful recipe to determine the number of classes (k) is the “2 to the k rule.” such that 2 k > n. There were 80 vehicles sold. So n = 80. If we try k = 6, which means we would use 6 classes, then 2 6 = 64, somewhat less than 80. Hence, 6 is not enough classes. If we let k = 7, then 2 7 128, which is greater than 80. So the recommended number of classes is 7. Step 2: Determine the class interval or width. The formula is: i  (H-L)/k where i is the class interval, H is the highest observed value, L is the lowest observed value, and k is the number of classes. ($35,925 - $15,546)/7 = $2,911 Round up to some convenient number, such as a multiple of 10 or 100. Use a class width of $3,000

6. 2-6 Constructing a Frequency Table - Example Step 3: Set the individual class limits

7. 2-7 Step 4: Tally the vehicle selling prices into the classes. Step 5: Count the number of items in each class. Constructing a Frequency Table

8. 2-8 Example 1. During 3 hours at Heathrow airport 55 aircraft arrived late. The number of minutes they were late is shown in the grouped frequency table below. Grouped Data 250 - 59 440 - 49 530 - 39 720 - 29 1010 - 19 270 - 9 frequencyminutes late Data is grouped into 6 class intervals of width 10.

9. 2-9 Data is grouped into 8 class intervals of width 4. Example 2. A group of University students took part in a sponsored race. The number of laps completed is given in the table below. Grouped Data 136 - 40 231 – 35 2526 – 30 1721 – 25 2016 – 20 1511 – 15 96 – 10 21 - 5 frequency (x)number of laps

10. 2-10 Characteristics of Classes Class Limits; – smallest and largest observed values that can belong to a class Boundaries; – actual values that separate successive classes Intervals; – the distance spanned by the boundaries of a class Class Midpoint – the arithmetic mean of its class boundaries

11. 2-11 Relative Class Frequencies Class frequencies can be converted to relative class frequencies to show the fraction of the total number of observations in each class. A relative frequency captures the relationship between a class total and the total number of observations.

12. 2-12 Relative Frequency Distribution To convert a frequency distribution to a relative frequency distribution, each of the class frequencies is divided by the total number of observations.

13. 2-13 Graphic Presentation of a Frequency Distribution The three commonly used graphic forms are: Histograms Frequency polygons Cumulative frequency distributions

14. 2-14 Histogram HISTOGRAM A graph in which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars and the bars are drawn adjacent to each other.

15. 2-15 Histogram Using Excel

16. 2-16 Distribution Shape: Skewness n Symmetric (not skewed) Skewness is zero. Skewness is zero. Mean and median are equal. Mean and median are equal. Relative Frequency.05.10.15.20.25.30.35 0 0 Skewness = 0 Skewness = 0

17. 2-17 Distribution Shape: Skewness Moderately Skewed Left – Skewness is negative. – Mean will usually be less than the median. Relative Frequency.05.10.15.20.25.30.35 0 0 Skewness = .31 Skewness = .31

18. 2-18 Distribution Shape: Skewness Moderately Skewed Right – Skewness is positive. – Mean will usually be more than the median. Relative Frequency.05.10.15.20.25.30.35 0 0 Skewness =.31 Skewness =.31

19. 2-19 Distribution Shape: Skewness n Highly Skewed Right Skewness is positive (often above 1.0). Skewness is positive (often above 1.0). Mean will usually be more than the median. Mean will usually be more than the median. Relative Frequency.05.10.15.20.25.30.35 0 0 Skewness = 1.25 Skewness = 1.25

20. 2-20 Seventy efficiency apartments Seventy efficiency apartments were randomly sampled in a small college town. The monthly rent prices for these apartments are listed in ascending order on the next slide. Distribution Shape: Skewness n Example: Apartment Rents

21. 2-21 Distribution Shape: Skewness

22. 2-22 Relative Frequency.05.10.15.20.25.30.35 0 0 Skewness =.92 Skewness =.92 Distribution Shape: Skewness

23. 2-23 Frequency Polygon A frequency polygon also shows the shape of a distribution and is similar to a histogram. It consists of line segments connecting the points formed by the intersections of the class midpoints and the class frequencies.

24. 2-24 Histogram Versus Frequency Polygon Both provide a quick picture of the main characteristics of the data (highs, lows, points of concentration, etc.) The histogram has the advantage of depicting each class as a rectangle, with the height of the rectangular bar representing the number in each class. The frequency polygon has an advantage over the histogram. It allows us to compare directly two or more frequency distributions.

25. 2-25 Cumulative Frequency Distribution

26. 2-26 Cumulative Frequency Distribution