1. Section 3.1 & 3.2 Preview & Measures of Center

2. Important Statistics Mean, median, standard deviation, variance Understanding and Interpreting important statistics Preview

3. Descriptive Statistics In this chapter we’ll learn to summarize or describe the important characteristics of a known set of data Inferential Statistics In later chapters we’ll learn to use sample data to make inferences or generalizations about a population Preview

4. Section 3.2 Measures of Center

5. Measure of Center: the value at the center or middle of a data set. Arithmetic Mean (Mean): the measure of center obtained by adding the values and dividing the total by the number of values (What most people call an average.)

6. Notation  denotes the sum of a set of values. x is the variable usually used to represent the individual data values. n represents the number of data values in a sample. N represents the number of data values in a population.

7. µ is pronounced ‘mu’ and denotes the mean of all values in a population Notation is pronounced ‘x-bar’ and denotes the mean of a set of sample values

8. Advantages - Is relatively reliable -means of samples drawn from the same population don’t vary as much as other measures of center - Takes every data value into account Mean Disadvantage Is sensitive to every data value, one extreme value can affect it dramatically; is not a resistant measure of center

9. Median: the middle value when the original data values are arranged in order of increasing (or decreasing) magnitude  Often denoted by x (pronounced “x-tilde”)  Is not affected by an extreme value (is a resistant measure of center) Median ~

10. First sort the values (arrange them in order), the follow one of these: If the number of data values is odd, the median is the number located in the exact middle of the list. If the number of data values is even, the median is found by computing the mean of the two middle numbers. Finding the Median

11. 5.401.100.42 0.73 0.481.10 0.66 → not in ascending order 0.420.48 0.660.731.10 1.10 5.40 → in ascending order (in order - odd number of values) exact middle MEDIAN is 0.73 5.401.100.42 0.73 0.481.10 → not in ascending order 0.420.48 0.731.10 1.10 5.40 → in ascending order 0.73 + 1.10 2 (in order - even number of values – no exact middle shared by two numbers) MEDIAN is 0.915

12. Example 1: The following are the heights of 7 teenage girls in inches: 586163646666700 Oops, that last student was supposed to be 70 inches. Without calculating, which measure of center (mean or median) will change?

13. Mode: the value that occurs with the greatest frequency Data set can have one, more than one, or no mode Mode Mode is the only measure of central tendency that can be used with nominal data Bimodal two data values occur with the same greatest frequency Multimodalmore than two data values occur with the same greatest frequency No Modeno data value is repeated

14. a. 5.40 1.10 0.42 0.73 0.48 1.10 b. 27 27 27 55 55 55 88 88 99 c.1 2 3 6 7 8 9 10  Mode is 1.10  Bimodal - 27 & 55  No Mode Find the mode of the following data sets:

15. Midrange: the value midway between the maximum and minimum values in the original data set Midrange

16. Sensitive to extremes because it uses only the maximum and minimum values, so rarely used but….. -Very easy to compute -Reinforces that there are several ways to define the center -Avoids confusion with the median Midrange

17. Round-off Rule for Measures of Center - Carry one more decimal place than is present in the original set of values.

18. Example 2: The Insurance Institute for Highway Safety conducted tests with crashes of new cars traveling at 6 mph. The total cost of the damages was found for a simple random sample of the tested cars and listed below. $7448$4911$9051$6374$4277 Find the (a) mean, (b) median, (c) mode, and (d) midrange.

19. Example 3: Listed below are the top 10 annual salaries (in millions of dollars) of TV personalities (based on data from OK! Magazine). 38363527151312109.68.4 Find the (a) mean, (b) median, (c) mode, and (d) midrange.

21. Part 2 Beyond the Basics of Measures of Center

22. *Assume that all sample values in each class are equal to the class midpoint. *Use class midpoint of classes for variable x. *Use frequencies of classes for variable f Mean from a Frequency Distribution

23. Example 4: Find the mean of the data summarized in the given frequency distribution. Tar (mg) in Nonfiltered Cigarettes Frequency (f) 10 – 131 14 – 170 18 – 2115 22 – 257 26 – 292 Σf = Class Midpoints (x)f·x Σ(f·x)

24. When data values are assigned different weights, we can compute a weighted mean. Multiply each weight (w) by the corresponding value (x), then add the products. Divide that total by the sum of the weights Weighted Mean x = w  (w x) 

25. Example 5: A student of the author earned grades of B, C, B, A, and D. Those courses had these corresponding numbers of credit hours: 3, 3, 4, 4, and 1. The grading system assigns quality points to letter grades as follows: A = 4, B = 3, C = 2, D = 1, F = 0. Compute the grade point average (GPA) and round the result with two decimal places. If the Dean’s list requires a GPA of 3.00 or greater, did this student make the Dean’s list? xwx*w Σ=

26. Best Measure of Center

27. Symmetric : distribution of data is symmetric if the left half of its histogram is roughly a mirror image of its right half Skewed: distribution of data is skewed if it is not symmetric and extends more to one side than the other Symmetric and Skewed

28. Skewed to the left : -also called negatively skewed -have a longer left tail -mean and median are to the left of the mode Skewed to the right : -also called positively skewed -have a longer right tail -mean and median are to the right of the mode Skewed Left or Right

29. Skewness

30. The mean and median cannot always be used to identify the shape of the distribution. Shape of the Distribution