1. Numerical Descriptive Measures

2. Summary Definitions
The central tendency is the extent to which all the data values group around a typical or central value.
The variation is the amount of dispersion, or scattering, of values
The shape is the pattern of the distribution of values from the lowest value to the highest value.

3. Measures of Central Tendency: The Mean
The arithmetic mean (often just called “mean”) is the most common measure of central tendency
For a sample of size n:
Pronounced x-bar
The ith value
Sample size
Observed values

4. Measures of Central Tendency: The Mean
(continued)
The most common measure of central tendency
Mean = sum of values divided by the number of values
Affected by extreme values (outliers)
Mean = 3
Mean = 4

5. Mean for Grouped Data Formula for Mean is given by Where
= Sum of cross products of frequency in each class with midpoint X of each class
n = Total number of observations (Total frequency) =

6. Mean for Grouped Data Example
Find the arithmetic mean for the following continuous
frequency distribution:
Class
Frequency

7. Solution for the Example
Applying the formula = 75.5/25=3.02

8. Mean
Class interval f
49.99 78 50
99.99
123
100
149.99
187
150
199.99 82
200
249.99 51
250
299.99 47
300
349.99 13
350
399.99 9
400
449.99 6
450
499.99 4
600

9. By taking mid values as 25, 75,… 475. Mean: 142.25
Class interval f
49.99 78 50
99.99
123
100
149.99
187
150
199.99 82
200
249.99 51
250
299.99 47
300
349.99 13
350
399.99 9
400
449.99 6
450
499.99 4
600
By taking mid values as 25, 75,… 475.
Mean:

10. Mean using coding:
Class f
0-7 2
Mean=x0 + w ((Summation of (u*f)) / n
w=numerical width of class interval
X0=value of midpoint assigned code 0

11. Mean using coding:
Class mid f Code (u) u*f 20
Mean=x0 + w ((Summation of (u*f)) / n
= (5) / 20 = 21.5
w=numerical width of class interval
X0=value of midpoint assigned code 0 5

12. Weighted mean:
Geometric mean:
Year Interest rate Growth factor Saving at the end of year
1 7%
Mean of growth factor = … )/ 5 = 1.11, corresponds to 11% rate.
100* (1.11)*(1.11) (1.11)*(1.11)* (1.11) = , correct growth rate should be less than 1.11.
GM = n (1.07*1.08*……….*1.18) 1/n
Product of x values =

13. Measures of Central Tendency: The Median
In an ordered array, the median is the “middle” number (50% above, 50% below)
Not affected by extreme values
Median = 3
Median = 3

14. Measures of Central Tendency: Locating the Median
The location of the median when the values are in numerical order (smallest to largest):
If the number of values is odd, the median is the middle number
If the number of values is even, the median is the average of the two middle numbers
Note that is not the value of the median, only the position of
the median in the ranked data

15. Median for Grouped Data
Formula for Median is given by
Median =
Where
L =Lower limit of the median class
n = Total number of observations =
m = Cumulative frequency preceding the median class
f = Frequency of the median class
c = Class interval of the median class

16. Median for Grouped Data Example
Find the median for the following continuous
frequency distribution:
Class
Frequency

17. Solution for the Example
Class Frequency Cumulative
Frequency
Total
Substituting in the formula the relevant values,
Median = , we have Median = =

18. Find median 300th = 126.17 301st=126.44 Class interval f 49.99 78 50
49.99 78 50
99.99
123
100
149.99
187
150
199.99 82
200
249.99 51
250
299.99 47
300
349.99 13
350
399.99 9
400
449.99 6
450
499.99 4
600
300th =
301st=126.44

19. Measures of Central Tendency: The Mode
Value that occurs most often
Not affected by extreme values
Used for either numerical or categorical data
There may be no mode
There may be several modes
No Mode
Mode = 9

20. Mode for Grouped Data Mode = Where L =Lower limit of the modal class
= Frequency of the modal class
= Frequency preceding the modal class
= Frequency succeeding the modal class
C = Class Interval of the modal class

21. Mode for Grouped Data Example
Example: Find the mode for the following
continuous frequency distribution:
Class
Frequency

22. Solution for the Example
Class Frequency
Total
Mode =
L = 2
= 8-4 = 4
= 8-7 = 1
C = 1 Hence Mode =
= 2.8

23. Measures of Central Tendency: Which Measure to Choose?
The mean is generally used, unless extreme values (outliers) exist.
The median is often used, since the median is not sensitive to extreme values. For example, median home prices may be reported for a region; it is less sensitive to outliers.
In some situations it makes sense to report both the mean and the median.

24. Measures of Central Tendency: Summary
Arithmetic Mean
Median
Mode
Most frequently observed value
Middle value in the ordered array

25. Coefficient of Variation
Measures of Variation
Variation
Standard Deviation
Coefficient of Variation
Range
Variance
Measures of variation give information on the spread or variability or dispersion of the data values.
Same center,
different variation

26. Measures of Variation: The Range
Simplest measure of variation
Difference between the largest and the smallest values:
Range = Xlargest – Xsmallest
Example:
Range = = 13

27. Measures of Variation: Why The Range Can Be Misleading
Ignores the way in which data are distributed
Sensitive to outliers
Range = = 5
Range = = 5
1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,3,3,3,3,4,5
Range = = 4
1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,3,3,3,3,4,120
Range = = 119

28. Interfractile range: Median is .5 fractile.
First third Second third Last third
2/3 fractile
1/3 fractile
If we divide data in??????? deciles , quartile and percentile
Interquartile range: Q3-Q1

29. Measures of Variation: The Variance
Average (approximately) of squared deviations of values from the mean
Sample variance:
Where
= arithmetic mean
n = sample size
Xi = ith value of the variable X

30. Measures of Variation: The Standard Deviation
Most commonly used measure of variation
Shows variation about the mean
Is the square root of the variance
Has the same units as the original data
Sample standard deviation:

31. Measures of Variation: The Standard Deviation
Steps for Computing Standard Deviation
1. Compute the difference between each value and the mean.
2. Square each difference.
3. Add the squared differences.
4. Divide this total by n-1 to get the sample variance.
5. Take the square root of the sample variance to get the sample standard deviation.

32. Measures of Variation: Sample Standard Deviation: Calculation Example
Sample Data (Xi) :
n = Mean = X = 16

34. Find S.D. Class Frequency 700-799 4 800-899 7 900 8 1000 10 1100 12
1200 17
1300 13
1400
1500 9
1600
1700 2 1
Find S.D.

35. Measures of Variation: Comparing Standard Deviations
Data A
Mean = 15.5
S = 3.338
Data B
Mean = 15.5
S = 0.926
Data C
Mean = 15.5
S = 4.570

36. Measures of Variation: Comparing Standard Deviations
Smaller standard deviation
Larger standard deviation

37. Standard Deviation for Grouped Data-Example
Frequency Distribution of Return on Investment of Mutual Funds
Return on Investment
Number of Mutual Funds
5-10
10-15
15-20
20-25
25-30
Total 10 12 16 14 8 60

38. Solution for the Example

39. Solution for the Example
From the spreadsheet of Microsoft Excel in the previous
slide, it is easy to see
Mean = =1040/60=17.333(cell F10),
Standard Deviation = S = = = 6.44
(Cell H12)

40. Measures of Variation: Summary Characteristics
The more the data are spread out, the greater the range, variance, and standard deviation.
The more the data are concentrated, the smaller the range, variance, and standard deviation.
If the values are all the same (no variation), all these measures will be zero.
None of these measures are ever negative.

41. Measures of Variation: The Coefficient of Variation
Measures relative variation
Always in percentage (%)
Shows variation relative to mean
Can be used to compare the variability of two or more sets of data measured in different units

42. Measures of Variation: Comparing Coefficients of Variation
Stock A:
Average price last year = $50
Standard deviation = $5
Stock B:
Average price last year = $100

43. Measures of Variation: Comparing Coefficients of Variation
Stock A:
Average price last year = $50
Standard deviation = $5
Stock B:
Average price last year = $100
Both stocks have the same standard deviation, but stock B is less variable relative to its price

44. Shape of a Distribution
Describes how data are distributed
Measures of shape
Symmetric or skewed
Left-Skewed(Negative))
Symmetric
Right-Skewed (Positive)
Mean < Median
Mean = Median
Median < Mean