chapter 11 hypothesis tests and estimation for population ... · population variance ... chapter 11...
TRANSCRIPT
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-1
Business Statistics
Department of Quantitative Methods & Information Systems
Dr. Mohammad Zainal QMIS 220
Chapter 11
Hypothesis Tests and Estimation
for Population Variances
Chapter Goals
After completing this chapter, you should be
able to:
Formulate and complete hypothesis tests for a single
population variance
Find critical chi-square distribution values from the
chi-square table
Formulate and complete hypothesis tests for the
difference between two population variances
Use the F table to find critical F values
QMIS 220, by Dr. M. Zainal Chap 11-2
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-2
Hypothesis Tests for Variances
Hypothesis Tests
for Variances
Tests for a Single
Population Variance
Tests for Two
Population Variances
Chi-Square test statistic F test statistic
QMIS 220, by Dr. M. Zainal Chap 11-3
Single Population
Hypothesis Tests for Variances
Tests for a Single
Population Variance
Chi-Square test statistic
H0: σ2 = σ0
2
HA: σ2 ≠ σ02
H0: σ2 σ0
2
HA: σ2 < σ02
H0: σ2 ≤ σ0
2
HA: σ2 > σ02
* Two tailed test
Lower tail test
Upper tail test
QMIS 220, by Dr. M. Zainal Chap 11-4
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-3
Chi-Square Test Statistic
Hypothesis Tests for Variances
Tests for a Single
Population Variance
Chi-Square test statistic *
The chi-squared test statistic for
a Single Population Variance is:
2
22
σ
1)s(n
where
2 = standardized chi-square variable
n = sample size
s2 = sample variance
σ2 = hypothesized variance
QMIS 220, by Dr. M. Zainal Chap 11-5
The Chi-square Distribution
The chi-square distribution is a family of
distributions, depending on degrees of freedom
(Like the t distribution).
The chi-square distribution curve starts at the
origin and lies entirely to the right of the vertical
axis.
The chi-square distribution assumes
nonnegative values only, and these are denoted
by the symbol 2 (read as “chi-square”).
QMIS 220, by Dr. M. Zainal Chap 11-6
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-4
The Chi-square Distribution
The shape of a specific chi-square distribution
depends on the number of degrees of freedom.
peak of a 2 distribution curve with 1 or 2
degrees of freedom occurs at zero and for a
curve with 3 or more degrees of freedom at
(df−2).
0 4 8 12 16 20 24 28 0 4 8 12 16 20 24 28 0 4 8 12 16 20 24 28
d.f. = 1 d.f. = 5 d.f. = 15
2 2 2
QMIS 220, by Dr. M. Zainal Chap 11-7
Finding the Critical Value
The critical value, , is found from the
chi-square table
Do not reject H0 Reject H0
2
2
2
H0: σ2 ≤ σ0
2
HA: σ2 > σ02
Upper tail test:
QMIS 220, by Dr. M. Zainal Chap 11-8
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-5
Finding the Critical Value
QMIS 220, by Dr. M. Zainal Chap 11-9
Finding the Critical Value
QMIS 220, by Dr. M. Zainal Chap 11-10
Example: Find the value of 2 for 7 degrees of freedom and an
area of .10 in the right tail of the chi-square distribution curve.
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-6
Finding the Critical Value
QMIS 220, by Dr. M. Zainal Chap 11-11
Example: Find the value of 2 for 9 degrees of freedom and an
area of .05 in the left tail of the chi-square distribution curve.
Example
A commercial freezer must hold the selected
temperature with little variation. Specifications call
for a standard deviation of no more than 4 degrees
(or variance of 16 degrees2). A sample of 16
freezers is tested and
yields a sample variance
of s2 = 24. Test to see
whether the standard
deviation specification
is exceeded. Use
= .05
QMIS 220, by Dr. M. Zainal Chap 11-12
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-7
Finding the Critical Value
Use the chi-square table to find the critical value:
Do not reject H0 Reject H0
= .05
2
2
2
= 24.9958
= 24.9958 ( = .05 and 16 – 1 = 15 d.f.)
22.516
1)24(16
σ
1)s(n2
22
The test statistic is:
Since 22.5 < 24.9958,
do not reject H0
There is not significant
evidence at the = .05 level
that the standard deviation
specification is exceeded
QMIS 220, by Dr. M. Zainal Chap 11-13
Lower Tail or Two Tailed Chi-square Tests
H0: σ2 = σ0
2
HA: σ2 ≠ σ02
H0: σ2 σ0
2
HA: σ2 < σ02
2/2
Do not reject H0 Reject
21-
2
Do not reject H0
Reject
/2
21-/2
2
/2
Reject
Lower tail test: Two tail test:
(2U) (2
L)
QMIS 220, by Dr. M. Zainal Chap 11-14
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-8
Confidence Interval Estimate for σ2
2/2
/2
21-/2
2
/2
(2U) (2
L)
The confidence interval estimate for σ2 is
2
L
22
2
U
2 1)s(nσ
1)s(n
χχ
Where 2L and 2
U are from the
2 distribution with n -1 degrees
of freedom
QMIS 220, by Dr. M. Zainal Chap 11-15
Example
A sample of 16 freezers yields a sample
variance of s2 = 24.
Form a 95% confidence interval for the
population variance.
QMIS 220, by Dr. M. Zainal Chap 11-16
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-9
Use the chi-square table to find 2L and 2
U :
6.2621
( = .05 and 16 – 1 = 15 d.f.)
Example (continued)
2.025
/2=.025
2.975
/2=.025
(2U) (2
L)
27.4884 57.489σ13.096
6.2621
1)24(16σ
27.4884
1)24(16
1)s(nσ
1)s(n
2
2
2
L
22
2
U
2
χχ
We are 95% confident that the population variance is between 13.096
and 57.489 degrees2. (Taking the square root, we are 95% confident that
the population standard deviation is between 3.619 and 7.582 degrees.)
QMIS 220, by Dr. M. Zainal Chap 11-17
Hypothesis Tests for Variances
Tests for Two
Population Variances
F test statistic
*
F Test for Difference in Two Population Variances
H0: σ12 = σ2
2
HA: σ12 ≠ σ2
2 Two tailed test
Lower tail test
Upper tail test
H0: σ12 σ2
2
HA: σ12 < σ2
2
H0: σ12 ≤ σ2
2
HA: σ12 > σ2
2
QMIS 220, by Dr. M. Zainal Chap 11-18
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-10
Hypothesis Tests for Variances
F test statistic *
F Test for Difference in Two Population Variances
Tests for Two
Population Variances 2
2
2
1
s
sF
The F test statistic is:
= Variance of Sample 1
D1 = n1 - 1 = numerator degrees of freedom
D2 = n2 - 1 = denominator degrees of freedom
= Variance of Sample 2
2
1s
2
2s
Where F has D1
numerator and D2
denominator
degrees of freedom
QMIS 220, by Dr. M. Zainal Chap 11-19
The F critical value is found from the F table
The are two appropriate degrees of freedom:
D1 (numerator) and D2 (denominator)
In the F table,
numerator degrees of freedom determine the column
denominator degrees of freedom determine the row
The F Distribution
where D1 = n1 – 1 ; D2 = n2 – 1 2
2
2
1
s
sF
QMIS 220, by Dr. M. Zainal Chap 11-20
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-11
The F distribution is continuous and skewed to the right.
The units of an F distribution, denoted by FD1,D2, are
nonnegative.
The F Distribution
QMIS 220, by Dr. M. Zainal Chap 11-21
Finding the F Value
QMIS 220, by Dr. M. Zainal Chap 11-22
Example: Find the F value for 4 degrees of freedom for the
numerator, 10 degrees of freedom for the denominator, and
0.1 area in the right tail of F distribution curve. (F .1, 4,10)
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-12
For a two-tailed test, always place the larger
sample variance in the numerator
For a one-tailed test, consider the alternative
hypothesis: place in the numerator the sample
variance for the population that is predicted
(based on HA) to have the larger variance
Formulating the F Ratio
where D1 = n1 – 1 ; D2 = n2 – 1 2
2
2
1
s
sF
QMIS 220, by Dr. M. Zainal Chap 11-23
F 0
rejection region for a one-tail test is
Finding the Critical Value
F 0
2/2
2
2
1 Fs
sF F
s
sF
2
2
2
1
(where the larger sample variance in the numerator)
rejection region for a two-tailed test is
/2
F F/2 Reject H0 Do not
reject H0
Reject H0 Do not reject H0
H0: σ12 = σ2
2
HA: σ12 ≠ σ2
2
H0: σ12 σ2
2
HA: σ12 < σ2
2
H0: σ12 ≤ σ2
2
HA: σ12 > σ2
2
QMIS 220, by Dr. M. Zainal Chap 11-24
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-13
F Test: An Example
You are a financial analyst for a brokerage firm. You
want to compare dividend yields between stocks listed
on the NYSE & NASDAQ. You collect the following data:
NYSE NASDAQ
Number 21 25
Mean 3.27 2.53
Std dev 1.30 1.16
Is there a difference in the
variances between the NYSE
& NASDAQ at the = 0.05 level?
QMIS 220, by Dr. M. Zainal Chap 11-25
F Test: Example Solution
Form the hypothesis test:
H0: σ21 = σ2
2 (there is no difference between variances)
HA: σ21 ≠ σ2
2 (there is a difference between variances)
Find the F critical value for = .05:
Numerator:
D1 = n1 – 1 = 21 – 1 = 20
Denominator:
D2 = n2 – 1 = 25 – 1 = 24
F.05/2, 20, 24 = 2.327
QMIS 220, by Dr. M. Zainal Chap 11-26
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-14
The test statistic is:
0
256.116.1
30.1
s
sF
2
2
2
2
2
1
/2 = .025
F/2
=2.327
Reject H0 Do not reject H0
H0: σ12 = σ2
2
HA: σ12 ≠ σ2
2
F Test: Example Solution
F = 1.256 is not greater than
the critical F value of 2.327, so
we do not reject H0
(continued)
Conclusion: There is no evidence of a
difference in variances at = .05
QMIS 220, by Dr. M. Zainal Chap 11-27
Using EXCEL
EXCEL
F test for two variances:
Data | Data Analysis | F-test: Two Sample for Variances
QMIS 220, by Dr. M. Zainal Chap 11-28
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-15
Chapter Summary
Performed chi-square tests for the variance
Used the chi-square table to find chi-square
critical values
Performed F tests for the difference between two
population variances
Used the F table to find F critical values
QMIS 220, by Dr. M. Zainal Chap 11-29
Problems
QMIS 220, by Dr. M. Zainal
Suppose a sample of 30 ECC students are given an IQ test. If
the sample has a standard deviation of 12.23 points, find a
90% confidence interval for the population standard deviation.
Chap 11-30
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-16
Problems
QMIS 220, by Dr. M. Zainal Chap 11-31
Problems
QMIS 220, by Dr. M. Zainal
A random sample of 10 hot drinks from Dispenser A had a
mean volume of 203 ml and a standard deviation of 3 ml.
Another random sample of 15 hot drinks from Dispenser B
gave corresponding values of 206 ml and 5 ml. The amount
dispensed by each machine may be assumed to be normally
distributed. Test, at the 5% significance level, the hypothesis
that there is no difference in the variability of the volume
dispensed by the two machines.
Chap 11-32
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-17
QMIS 220, by Dr. M. Zainal Chap 11-33
QMIS 220, by Dr. M. Zainal Chap 11-34
QMIS 220, by Dr. M. Zainal
Chapter 11 Student Lecture Notes 11-18
Copyright
The materials of this presentation were mostly
taken from the PowerPoint files accompanied
Business Statistics: A Decision-Making Approach,
7e © 2008 Prentice-Hall, Inc.
QMIS 220, by Dr. M. Zainal Chap 11-35