1. LESSON 3: CENTRAL TENDENCY
Outline
Arithmetic mean, median and mode
Ungrouped data
Grouped data
Percentiles, fractiles, and quartiles

2. MEASURES OF CENTRAL LOCATION MEAN
Mean is defined as follows:
Sum of the measurements
Mean =
Number of measurements
In the following, sample mean and population means are discussed separately.
Note the difference of notation - sample mean is denote by and the population mean is denoted by . The number of values in a sample is denoted by n and the number of values in the population is denoted by N.

3. MEASURES OF CENTRAL LOCATION MEAN
Mean of
Data Set
Data Set is
Sample
Population
Mean

4. MEASURES OF CENTRAL LOCATION SAMPLE MEAN
The sample mean is the sum of all the sample values divided by the number of sample values:
where stands for the sample mean
n is the total number of values in the sample
is the value of the i-th observation
represents a summation

5. MEASURES OF CENTRAL LOCATION SAMPLE MEAN
Statistic: a measurable characteristic of a sample.
A sample of five executives received the following amounts of bonus last year: $12,000, $14,000, $18,000, $17,000, and $19,000. Find the average bonus for these five executives.
Since these values represent a sample size of 5, the sample mean is
(12, , , , ,000)/5 =

6. MEASURES OF CENTRAL LOCATION SAMPLE MEAN
Sample mean approximated from grouped data:
Where is the sample mean
is the frequency of the th class interval
is the midpoint of the th class interval
is the total number of observations,
represents a summation

7. MEASURES OF CENTRAL LOCATION SAMPLE MEAN
Compute the average days to maturity of 40 investments from the following frequency distribution:

8. MEASURES OF CENTRAL LOCATION POPULATION MEAN
The population mean is the sum of all the population values divided by the number of population values:
Where  stands for the population mean
N is the total number of values in the population
is the value of the i-th observation
represents a summation

9. MEASURES OF CENTRAL LOCATION POPULATION MEAN
Parameter: a measurable characteristic of a population.
The Keller family owns four cars. The following is the mileage attained by each car: 55,000, 25,000, 40,000, and 80,000. Find the average miles covered by each car.
The mean is
(55, , , ,000)/4 =

10. MEASURES OF CENTRAL LOCATION PROPERTIES OF MEAN
Data possessing an interval scale or a ratio scale, usually have a mean.
All the values are included in computing the mean.
A set of data has a unique mean.
The mean is affected by unusually large or small data values.
The arithmetic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is zero.

11. MEASURES OF CENTRAL LOCATION PROPERTIES OF MEAN
Consider the set of values: 3, 8, and 4. The mean is 5. Illustrating the fifth property, (3-5) + (8-5) + (4-5) = = 0. In other words,

12. MEASURES OF CENTRAL LOCATION MEDIAN
Median: The midpoint of the values after they have been ordered from the smallest to the largest, or the largest to the smallest.
There are as many values above the median as below it in the data array.
For an even set of numbers, the median will be the arithmetic average of the two middle numbers.
Median is denoted by

13. MEASURES OF CENTRAL LOCATION MEDIAN
After data are ordered
If is odd median is the number
If is even median is the arithmetic average of
and number

14. MEASURES OF CENTRAL LOCATION MEDIAN
The median is the most appropriate measure of central location to use when the data under consideration are ranked data, rather than quantitative data.
For example, if 13 universities are ranked according to the reputation, university 7 is the one of median reputation.

15. MEASURES OF CENTRAL LOCATION MEDIAN
Median is used when few extreme values influence mean too much. For example, one rich family may affect the mean income. So, median income is often reported in place of mean income.
Median is used when all values are not available. For example, in life testing the experiment may end before generating all values. So, mean may not be calculated and median is used instead.

16. MEASURES OF CENTRAL LOCATION MEDIAN
Compute the median for the following data.
The age of a sample of five college students is: 21, 25, 19, 20, and 22.
Arranging the data in ascending order gives:
Thus the median is

17. MEASURES OF CENTRAL LOCATION MEDIAN
Compute the median for the following data.
The height of four basketball players, in inches, is 76, 73, 80, and 75.
Arranging the data in ascending order gives:
Thus the median is

18. MEASURES OF CENTRAL LOCATION MODE
The mode is the value of the observation that appears most frequently.
The mode is most useful when an important aspect of describing the data involves determining the number of times each value occurs. If the data are qualitative (e.g., number of graduate in mechanical, automotive, industrial, etc.) then, mode is useful (e.g., a modal class is mechanical).
For grouped data, mode is the midpoint of the class interval of the highest frequency.

19. MEASURES OF CENTRAL LOCATION MODE
EXAMPLE: The exam scores for ten students are: 81, 93, 84, 75, 68, 87, 81, 75, 81, 87.
The modal score =

20. MEASURES OF CENTRAL LOCATION MODE
Find the mode for the following grouped data on days to maturity of 40 investments

22. MEASURES OF CENTRAL LOCATION MEAN, MEDIAN, MODE
Mean: affected by unusually large/small data, may be used if the data are quantitative (ratio or interval scale).
Median: most appropriate if the data are ranked (ordinal scale)
Mode: most appropriate if the data are qualitative (nominal scale)
Appropriate measures if the data has
ratio or interval scale: mean, median, mode
ordinal scale: median, mode
nominal scale: mode

23. FINDING MEDIAN AND MODE FROM AN ORDERED STEM-AND-LEAF PLOT
Find the median and mode from the following ordered stem-and-leaf plot on days to maturity of 40 investments Stem Leaves

24. MEASURES OF CENTRAL LOCATION RELATIVE VALUES OF MEAN, MEDIAN, MODE
Mode<Median<Mean
If distribution is
positively skewed
Mode=Median=Mean
If distribution is
symmetric
Mean<Median<Mode
if distribution is
negatively skewed

25. RELATIVE STANDING PERCENTILES, FRACTILES, QUARTILES
Percentiles divide the distribution into 100 groups.
A percentile is a point below which a stated percentage of observations lie.
The p-th percentile is a point below which p% of the values lie.
For example, if the 78th percentile of GMAT scores is 600, then 78% scores are below 600.
Percentiles are not unique. For example, if 78% scores are below 600 and 82% scores are below 610, then the 78th percentile may be any point above 600 and below 610.

26. RELATIVE STANDING PERCENTILES, FRACTILES, QUARTILES
Alternate to percentile is fractile.
A fractile is a point below which a stated fraction of observations lie.
The d fractile, is a point below which 100d% of the values lie.
For example, if the 0.78 fractile of GMAT scores is 600, then 78% scores are below 600. Alternate to the 78th percentile is 0.78 fractile. In this case,

27. RELATIVE STANDING PERCENTILES, FRACTILES, QUARTILES
Quartiles divide data into four groups of equal frequency.
First quartile = 25th percentile = 0.25 fractile =
Second quartile = 50th percentile = 0.50 fractile =
= median
Third quartile = 75th percentile = 0.75 fractile =

28. RELATIVE STANDING PROCEDURE TO FIND A GIVEN PERCENTILE
Procedure to find Assume
Step 1: Sort the data in the ascending order (low to high)
Step 2: Find which is the largest integer such that
Step 3: Compute the d fractile i.e., 100d-th percentile as follows
Note: Step 3 finds the required percentile by interpolating between and

29. RELATIVE STANDING PROCEDURE TO FIND A GIVEN PERCENTILE
Example: Consider data set 2, 3, 5, 6, 8, 10, 12, 15, 18, 20.
Find the 20th percentile
Note: the data set is already ordered. So, Step 1 is not necessary.
Step 2: Find the largest integer
So,
Step 3: Compute

30. RELATIVE STANDING PROCEDURE TO FIND A GIVEN PERCENTILE
Example: Consider data set 2, 3, 5, 6, 8, 10, 12, 15, 18, 20.
Find the 75th percentile
Note: the data set is already ordered. So, Step 1 is not necessary.
Step 2: Find the largest integer
So,
Step 3: Compute

31. RELATIVE STANDING PROCEDURE TO FIND A GIVEN PERCENTILE
Find the 80th percentile from the following ordered stem-and-leaf plot on days to maturity of 40 investments Stem Leaves

32. RELATIVE STANDING: GROUPED DATA PROCEDURE TO FIND A GIVEN PERCENTILE
For the grouped data, read the percentiles directly from the graph for the cumulative relative frequency distribution.
Find the 80th percentile from the graph for the cumulative relative frequency distribution shown on the next slide and constructed from the data on days to maturity of 40 investments.

33. OGIVE
CUMULATIVE RELATIVE FREQUENCY GRAPH
1.000
1.000
0.900
0.800
0.725
0.600
Cumulative Frequency
0.550
0.400
0.300
0.200
0.100
0.075
0.000 40 50 60 70 80 90
100
Number of Days to Maturity

34. READING AND EXERCISES Lesson 3 Reading: Section 2-2, pp. 38-47
2-18, 2-20 (and 2-4a), 2-26