chapter 12 analysis of variance. 2 the f distribution definition 1. the f distribution is continuous...

Chapter 12

ANALYSIS OF VARIANCE

2

THE F DISTRIBUTION

Definition 1. The F distribution is continuous and

skewed to the right.2. The F distribution has two numbers of

degrees of freedom: df for the numerator and df for the denominator.

3. The units of an F distribution, denoted F, are nonnegative.

3

THE F DISTRIBUTION cont.

df = (8, 14)

First number denotes the df for the numerator

Second number denotes the df for the denominator

4

Figure 12.1 Three F distribution curves.

df = (1 , 3)

df = (7 , 6)

df = (12 , 40)

F

5

Example 12-1

Find the F value for 8 degrees of freedom for the numerator, 14 degrees of freedom for the denominator, and .05 area in the right tail of the F distribution curve.

6

Solution 12-1

Degrees of Freedom for the Numerator

1 2 . . . 8 . . . 100

12.

14.

100

161.518.51. . . 4.60. . . 3.94

199.519.00. . . 3.74. . . 3.09

. . .

. . .

. . .

. . .

. . .

. . .

238.919.37. . . 2.70. . .2.03

. . .. . . . . .. . .. . .. . .

253.019.49. . .2.19. . .1.39D

eg

rees

of

Freed

om

for

the

Den

om

inato

r

Table 12.1

The F value for 8 df for the numerator, 14 df for the denominator, and .05 area in the right tail

7

Figure 12.2 The critical value of F for 8 df for the numerator, 14 df for the denominator, and .05 area in the right tail.

df = (8, 14)

.05

2.70 F 0

The required F value

8

ONE-WAY ANALYSIS OF VARIANCE

Calculating the Value of the Test Statistic

One-Way ANOVA Test

9

ONE-WAY ANALYSIS OF VARIANCE cont.

Definition ANOVA is a procedure used to test

the null hypothesis that the means of three or more populations are equal.

10

Assumptions of One-Way ANOVA

The following assumptions must hold true to use one-way ANOVA.

1. The populations from which the samples are drawn are (approximately) normally distributed.

2. The populations from which the samples are drawn have the same variance (or standard deviation).

3. The samples drawn from different populations are random and independent.

11

Calculating the Value of the Test Statistic

Test Statistic F for a One-Way ANOVA Test

The value of the test statistic F for an ANOVA test is calculated as

MSW

MSBor

samples within Variance

samplesbetween VarianceF

12

Example 12-2

Fifteen fourth-grade students were randomly assigned to three groups to experiment with three different methods of teaching arithmetic. At the end of the semester, the same test was given to all 15 students. The table gives the scores of students in the three groups.

13

Example 12-2

Calculate the value of the test statistic F. Assume that all the required assumptions mentioned earlier hold true

Method I Method II Method III

4873516587

5585706990

8468957467

14

Solution 12-2Let

x = the score of a student k = the number of different samples (or

treatments) ni = the size of sample i Ti = the sum of the values in sample i n = the number of values in all samples

= n1 + n2 + n3 + . . . Σx = the sum of the values in all samples

= T1 + T2 + T3 + . . . Σx² = the sum of the squares of the values in all

samples

15

Solution 12-2

To calculate MSB and MSW, we first compute the between-samples sum of squares denoted by SSB and the within-samples sum of squares denoted by SSW. The sum of SSB and SSW is called the total sum of squares and it is denoted by SST; that is,

SST = SSB + SSW

16

Between- and Within-Samples Sums of Squares

The between-samples sum of squares, denoted by SSB, is calculates as

n

x

n

T

n

T

n

TSSB

2

3

23

2

22

1

21

)(...

17

Between- and Within-Samples Sums of Squares cont.

The within-samples sum of squares, denoted by SSW, is calculated as

...

3

23

2

22

1

212

n

T

n

T

n

TxSSW

18

Table 12.2

Method I Method II Method III

4873516587

5585706990

8468957467

T1 = 324

n1 = 5

T2 = 369

n2 = 5

T3 = 388

n3 = 5

19

Solution 12-2

∑x = T1 + T2 + T3 = 1081

n = n1 + n2 + n3 = 15

Σx² = (48)² + (73)² + (51)² + (65)² + (87)² + (55)² + (85)² + (70)²

+ (69)² + (90)² + (84)² + (68)² + (95)² + (74)² + (67)²

= 80,709

20

Solution 12-2

9333.28048000.23721333.432SST

8000.23725

)388(

5

)369(

5

)324(709,80SSW

1333.43215

)1081(

5

)388(

5

)369(

5

)324(SSB

222

2222

21

Calculating the Values of MSB and MSW

MSB and MSW are calculated as

Where k – 1 and n – k are, respectively, the df for the numerator and the df for the denominator for the F distribution.

kn

SSWMSW

k

SSBMSB

and

1

22

Solution 12-2

09.17333.197

0667.216

7333.197315

8000.2372

0667.21613

432.1333

1

MSW

MSBF

kn

SSWMSW

k

SSBMSB

23

Table 12.3 ANOVA Table

Source of Variation

Degrees of Freedom

Sum of Squares

Mean Square

Value of the Test Statistic

BetweenWithin

k – 1

n – k

SSBSSW

MSBMSW

Total n – 1 SSTMSW

MSBF

24

Table 12.4 ANOVA Table for Example 12-2

Source of Variation

Degrees of Freedom

Sum of Squares

Mean Square

Value of the Test Statistic

BetweenWithin

2 12

432.13332372.8000

216.0667197.7333

Total 14 2804.9333

09.17333.197

0667.216F

25

One-Way ANOVA Test

Example 12-3 Reconsider Example 12-2 about the scores

of 15 fourth-grade students who were randomly assigned to three groups in order to experiment with three different methods of teaching arithmetic. At the 1% significance level, can we reject the null hypothesis that the mean arithmetic score of all fourth-grade students taught by each of these three methods is the same? Assume that all the assumptions required to apply the one-way ANOVA procedure hold true.

26

Solution 12-3

H0: μ1 = μ2 = μ3 The mean scores of the three groups are

equal H1: Not all three means are equal

27

Solution 12-3 α = .01 A one-way ANOVA test is always right-

tailed Area in the right tail is .01 df for the numerator = k – 1 = 3 – 1 = 2 df for the denominator = n – k = 15 – 3

= 12 The required value of F is 6.93

28

Figure 12.3 Critical value of F for df = (2,12) and α = .01.

F 0 6.93

Reject H0Do not reject H1

α = .01

Critical value of F

29

Solution 12-3

The value of the test statistic F = 1.09 It is less than the critical value of F =

6.93 If falls in the nonrejection region

Hence, we fail to reject the null hypothesis

30

Example 12-4 From time to time, unknown to its employees,

the research department at Post Bank observes various employees for their work productivity . Recently this department wanted to check whether the four tellers at a branch of this bank serve, on average, the same number of customers per hour. The research manager observed each of the four tellers for a certain number of hours. The following table gives the number of customers served by the four tellers during each of the observed hours.

31

Example 12-4

Teller A

Teller B

Teller C

Teller D

1921262418

141614131713

111421131618

2419212620

32

Example 12-4

At the 5% significance level, test the null hypothesis that the mean number of customers served per hour by each of these four tellers is the same. Assume that all the assumptions required to apply the one-way ANOVA procedure hold true.

33

Solution 12-4

H0: μ1 = μ2 = μ3 = μ4 The mean number of customers served

per hour by each of the four tellers is the same

H1: Not all four population means are equal

34

Solution 12-4

We are testing for the equality of four means for four normally distributed populations

We use the F distribution to make the test

35

Solution 12-4

α = .05. A one-way ANOVA test is always right-

tailed. Area in the right tail is .05. df for the numerator = k – 1 = 4 – 1 = 3 df for the denominator = n – k = 22 – 4

= 18

36

Figure 12.4 Critical value of F for df = (3, 18)

and α = .05.

F 0 3.16

Reject H0Do not reject H0

α = .05

Critical value of F

37

Table 12.5

Teller A Teller B Teller C Teller D

1921262418

141614131713

111421131618

2419212620

T1 = 108

n1 = 5

T2 = 87

n2 = 6

T3 = 93

n3 = 6

T4 = 110

n4 = 5

38

Solution 12-4 Σx = T1 + T2 + T3 + T4 =108 + 87 + 93 + 110

= 398 n = n1 + n2 + n3 + n4 = 5 + 6 + 6 + 5 = 22 Σx² = (19)² + (21)² + (26)² + (24)² + (18)² +

(14)² + (16)² + (14)² + (13)² + (17)² + (13)² + (11)² + (14)² + (21)² + (13)² + (16)² + (18)² + (24)² + (19)² + (21)² + (26)² + (20)²

= 7614

39

Solution 12-4

2000.1585

)110(

6

)93(

6

)87(

5

)108(7614

6182.25522

)398(

5

)110(

6

)93(

6

)87(

5

)108(

2222

4

24

3

23

2

22

1

212

22222

2

4

24

3

23

2

22

1

21

n

T

n

T

n

T

n

TxSSW

n

x

n

T

n

T

n

T

n

TSSB

40

Solution 12-4

69.97889.8

2061.85

7889.8422

2000.158

2061.8514

255.6182

1

MSW

MSBF

kn

SSWMSW

k

SSBMSB

41

Table 12.6 ANOVA Table for Example 12-4

Source of Variation

Degrees of Freedom

Sum of Squares

Mean Square

Value of the Test Statistic

BetweenWithin

3 18

255.6182158.2000

85.20618.7889

Total 21 413.8182

69.97889.8

2061.85F

42

Solution 12-4

The value for the test statistic F = 9.69 It is greater than the critical value of F If falls in the rejection region

Consequently, we reject the null hypothesis