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Hypothesis Testing with One Sample

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Title: Hypothesis Testing with One Sample


1
Chapter 7
  • Hypothesis Testing with One Sample

2
Chapter Outline
  • 7.1 Introduction to Hypothesis Testing
  • 7.2 Hypothesis Testing for the Mean (Large
    Samples)
  • 7.3 Hypothesis Testing for the Mean (Small
    Samples)
  • 7.4 Hypothesis Testing for Proportions
  • 7.5 Hypothesis Testing for Variance and Standard
    Deviation (Not in the Syllabus)

3
Section 7.1
  • Introduction to Hypothesis Testing

4
Section 7.1 Objectives
  • State a null hypothesis and an alternative
    hypothesis
  • Identify type I and type II errors and interpret
    the level of significance
  • Determine whether to use a one-tailed or
    two-tailed statistical test and find a p-value
  • Make and interpret a decision based on the
    results of a statistical test
  • Write a conclusion for a hypothesis test

5
Hypothesis Tests
  • Hypothesis test
  • A process that uses sample statistics to test a
    claim about the value of a population parameter.
  • For example An automobile manufacturer
    advertises that its new hybrid car has a mean
    mileage of 50 miles per gallon. To test this
    claim, a sample would be taken. If the sample
    mean differs enough from the advertised mean, you
    can decide the advertisement is wrong.

6
Hypothesis Tests
  • Statistical hypothesis
  • A statement, or claim, about a population
    parameter.
  • Need a pair of hypotheses
  • one that represents the claim
  • the other, its complement
  • When one of these hypotheses is false, the other
    must be true.

7
Stating a Hypothesis
  • Null hypothesis
  • A statistical hypothesis that contains a
    statement of equality such as ?, , or ?.
  • Denoted H0 read H subzero or H naught.
  • Alternative hypothesis
  • A statement of inequality such as gt, ?, or lt.
  • Must be true if H0 is false.
  • Denoted Ha read H sub-a.

8
Stating a Hypothesis
  • To write the null and alternative hypotheses,
    translate the claim made about the population
    parameter from a verbal statement to a
    mathematical statement.
  • Then write its complement.

H0 µ k Ha µ gt k
H0 µ k Ha µ lt k
H0 µ k Ha µ ? k
  • Regardless of which pair of hypotheses you use,
    you always assume µ k and examine the sampling
    distribution on the basis of this assumption.

9
Example Stating the Null and Alternative
Hypotheses
  • Write the claim as a mathematical sentence. State
    the null and alternative hypotheses and identify
    which represents the claim.
  • A university publicizes that the proportion of
    its students who graduate in 4 years is 82.

Solution
H0 Ha
Equality condition
(Claim)
p 0.82
Complement of H0
p ? 0.82
10
Example Stating the Null and Alternative
Hypotheses
  • Write the claim as a mathematical sentence.
    State the null and alternative hypotheses and
    identify which represents the claim.
  • A water faucet manufacturer announces that the
    mean flow rate of a certain type of faucet is
    less than 2.5 gallons per minute.

Solution
H0 Ha
Complement of Ha
µ 2.5 gallons per minute
Inequality condition
(Claim)
µ lt 2.5 gallons per minute
11
Example Stating the Null and Alternative
Hypotheses
  • Write the claim as a mathematical sentence.
    State the null and alternative hypotheses and
    identify which represents the claim.
  • A cereal company advertises that the mean weight
    of the contents of its 20-ounce size cereal boxes
    is more than 20 ounces.

Solution
H0 Ha
µ 20 ounces
Complement of Ha
Inequality condition
(Claim)
µ gt 20 ounces
12
Types of Errors
  • No matter which hypothesis represents the claim,
    always begin the hypothesis test assuming that
    the equality condition in the null hypothesis is
    true.
  • At the end of the test, one of two decisions will
    be made
  • reject the null hypothesis
  • fail to reject the null hypothesis
  • Because your decision is based on a sample, there
    is the possibility of making the wrong decision.

13
Types of Errors
Actual Truth of H0 Actual Truth of H0
Decision H0 is true H0 is false
Do not reject H0 Correct Decision Type II Error
Reject H0 Type I Error Correct Decision
  • A type I error occurs if the null hypothesis is
    rejected when it is true.
  • A type II error occurs if the null hypothesis is
    not rejected when it is false.

14
Example Identifying Type I and Type II Errors
  • The USDA limit for salmonella contamination for
    chicken is 20. A meat inspector reports that the
    chicken produced by a company exceeds the USDA
    limit. You perform a hypothesis test to determine
    whether the meat inspectors claim is true. When
    will a type I or type II error occur? Which is
    more serious? (Source United States Department
    of Agriculture)

15
Solution Identifying Type I and Type II Errors
  • Let p represent the proportion of chicken that is
    contaminated.

H0 Ha
Hypotheses
p 0.2
p gt 0.2
(Claim)
16
Solution Identifying Type I and Type II Errors
H0 Ha
Hypotheses
p 0.2
(Claim)
p gt 0.2
A type I error is rejecting H0 when it is true.
The actual proportion of contaminated chicken is
less than or equal to 0.2, but you decide to
reject H0.
A type II error is failing to reject H0 when it
is false.
The actual proportion of contaminated chicken is
greater than 0.2, but you do not reject H0.
17
Solution Identifying Type I and Type II Errors
H0 Ha
Hypotheses
p 0.2
(Claim)
p gt 0.2
  • With a type I error, you might create a health
    scare and hurt the sales of chicken producers who
    were actually meeting the USDA limits.
  • With a type II error, you could be allowing
    chicken that exceeded the USDA contamination
    limit to be sold to consumers.
  • A type II error could result in sickness or even
    death.

18
Level of Significance
  • Level of significance
  • Your maximum allowable probability of making a
    type I error.
  • Denoted by ?, the lowercase Greek letter alpha.
  • By setting the level of significance at a small
    value, you are saying that you want the
    probability of rejecting a true null hypothesis
    to be small.
  • Commonly used levels of significance
  • ? 0.10 ? 0.05 ? 0.01
  • P(type II error) ß (beta)

19
Statistical Tests
  • After stating the null and alternative hypotheses
    and specifying the level of significance, a
    random sample is taken from the population and
    sample statistics are calculated.
  • The statistic that is compared with the parameter
    in the null hypothesis is called the test
    statistic.

20
P-values
  • P-value (or probability value)
  • The probability, if the null hypothesis is true,
    of obtaining a sample statistic with a value as
    extreme or more extreme than the one determined
    from the sample data.
  • Depends on the nature of the test.

21
Nature of the Test
  • Three types of hypothesis tests
  • left-tailed test
  • right-tailed test
  • two-tailed test
  • The type of test depends on the region of the
    sampling distribution that favors a rejection of
    H0.
  • This region is indicated by the alternative
    hypothesis.

22
Left-tailed Test
  • The alternative hypothesis Ha contains the
    less-than inequality symbol (lt).

H0 µ ? k Ha µ lt k
23
Right-tailed Test
  • The alternative hypothesis Ha contains the
    greater-than inequality symbol (gt).

H0 µ k Ha µ gt k
24
Two-tailed Test
  • The alternative hypothesis Ha contains the not
    equal inequality symbol (?). Each tail has an
    area of ½P.

H0 µ k Ha µ ? k
25
Example Identifying The Nature of a Test
  • For each claim, state H0 and Ha. Then determine
    whether the hypothesis test is a left-tailed,
    right-tailed, or two-tailed test. Sketch a normal
    sampling distribution and shade the area for the
    P-value.
  • A university publicizes that the proportion of
    its students who graduate in 4 years is 82.

Solution
p 0.82
H0 Ha
p ? 0.82
Two-tailed test
26
Example Identifying The Nature of a Test
  • For each claim, state H0 and Ha. Then determine
    whether the hypothesis test is a left-tailed,
    right-tailed, or two-tailed test. Sketch a normal
    sampling distribution and shade the area for the
    P-value.
  • A water faucet manufacturer announces that the
    mean flow rate of a certain type of faucet is
    less than 2.5 gallons per minute.

Solution
µ 2.5 gpm
H0 Ha
µ lt 2.5 gpm
Left-tailed test
27
Example Identifying The Nature of a Test
  • For each claim, state H0 and Ha. Then determine
    whether the hypothesis test is a left-tailed,
    right-tailed, or two-tailed test. Sketch a normal
    sampling distribution and shade the area for the
    P-value.
  • A cereal company advertises that the mean weight
    of the contents of its 20-ounce size cereal boxes
    is more than 20 ounces.

Solution
µ 20 oz
H0 Ha
µ gt 20 oz
Right-tailed test
28
Making a Decision
  • Decision Rule Based on P-value
  • Compare the P-value with ?.
  • If P ? ?, then reject H0.
  • If P gt ?, then fail to reject H0.

Claim Claim
Decision Claim is H0 Claim is Ha
Reject H0
Fail to Reject H0
There is enough evidence to reject the claim
There is enough evidence to support the claim
There is not enough evidence to reject the claim
There is not enough evidence to support the claim
29
Example Interpreting a Decision
  • You perform a hypothesis test for the following
    claim. How should you interpret your decision if
    you reject H0? If you fail to reject H0?
  • H0 (Claim) A university publicizes that the
    proportion of its students who graduate in 4
    years is 82.

30
Solution Interpreting a Decision
  • The claim is represented by H0.
  • If you reject H0 you should conclude there is
    sufficient evidence to indicate that the
    universitys claim is false.
  • If you fail to reject H0, you should conclude
    there is insufficient evidence to indicate that
    the universitys claim (of a four-year graduation
    rate of 82) is false.

31
Example Interpreting a Decision
  • You perform a hypothesis test for the following
    claim. How should you interpret your decision if
    you reject H0? If you fail to reject H0?
  • Ha (Claim) Consumer Reports states that the mean
    stopping distance (on a dry surface) for a Honda
    Civic is less than 136 feet.
  • Solution
  • The claim is represented by Ha.
  • H0 is the mean stopping distanceis greater than
    or equal to 136 feet.

32
Solution Interpreting a Decision
  • If you reject H0 you should conclude there is
    enough evidence to support Consumer Reports
    claim that the stopping distance for a Honda
    Civic is less than 136 feet.
  • If you fail to reject H0, you should conclude
    there is not enough evidence to support Consumer
    Reports claim that the stopping distance for a
    Honda Civic is less than 136 feet.

33
Steps for Hypothesis Testing
  • State the claim mathematically and verbally.
    Identify the null and alternative hypotheses.
  • H0 ? Ha ?
  • Specify the level of significance.
  • a ?
  • Determine the standardized sampling distribution
    and draw its graph.
  • Calculate the test statisticand its standardized
    value.Add it to your sketch.

34
Steps for Hypothesis Testing
  1. Find the P-value.
  2. Use the following decision rule.
  3. Write a statement to interpret the decision in
    the context of the original claim.

Is the P-value less than or equal to the level of
significance?
Fail to reject H0.
Reject H0.
35
Section 7.1 Summary
  • Stated a null hypothesis and an alternative
    hypothesis
  • Identified type I and type II errors and
    interpreted the level of significance
  • Determined whether to use a one-tailed or
    two-tailed statistical test and found a p-value
  • Made and interpreted a decision based on the
    results of a statistical test
  • Wrote a claim for a hypothesis test

36
Section 7.2
  • Hypothesis Testing for the Mean (Large Samples)

37
Section 7.2 Objectives
  • Find P-values and use them to test a mean µ
  • Use P-values for a z-test
  • Find critical values and rejection regions in a
    normal distribution
  • Use rejection regions for a z-test

38
Using P-values to Make a Decision
  • Decision Rule Based on P-value
  • To use a P-value to make a conclusion in a
    hypothesis test, compare the P-value with ?.
  • If P ? ?, then reject H0.
  • If P gt ?, then fail to reject H0.

39
Example Interpreting a P-value
  • The P-value for a hypothesis test is P 0.0237.
    What is your decision if the level of
    significance is
  • 0.05?
  • 0.01?

SolutionBecause 0.0237 lt 0.05, you should
reject the null hypothesis.
Solution Because 0.0237 gt 0.01, you should fail
to reject the null hypothesis.
40
Finding the P-value
  • After determining the hypothesis tests
    standardized test statistic and the test
    statistics corresponding area, do one of the
    following to find the P-value.
  • For a left-tailed test, P (Area in left tail).
  • For a right-tailed test, P (Area in right
    tail).
  • For a two-tailed test, P 2(Area in tail of test
    statistic).

41
Example Finding the P-value
  • Find the P-value for a left-tailed hypothesis
    test with a test statistic of z -2.23. Decide
    whether to reject H0 if the level of significance
    is a 0.01.

SolutionFor a left-tailed test, P (Area in
left tail)
P 0.0129
Because 0.0129 gt 0.01, you should fail to reject
H0
42
Example Finding the P-value
  • Find the P-value for a two-tailed hypothesis test
    with a test statistic of z 2.14. Decide whether
    to reject H0 if the level of significance is a
    0.05.

SolutionFor a two-tailed test, P 2(Area in
tail of test statistic)
1 0.9838 0.0162
P 2(0.0162) 0.0324
0.9838
Because 0.0324 lt 0.05, you should reject H0
43
Z-Test for a Mean µ
  • Can be used when the population is normal and ?
    is known, or for any population when the sample
    size n is at least 30.
  • The test statistic is the sample mean
  • The standardized test statistic is z
  • When n ? 30, the sample standard deviation s can
    be substituted for ?.

44
Using P-values for a z-Test for Mean µ
In Words In Symbols
  1. State the claim mathematically and verbally.
    Identify the null and alternative hypotheses.
  2. Specify the level of significance.
  3. Determine the standardized test statistic.
  4. Find the area that corresponds to z.

State H0 and Ha.
Identify ?.
Use Table 4 in Appendix B.
45
Using P-values for a z-Test for Mean µ
In Words In Symbols
  • Find the P-value.
  • For a left-tailed test, P (Area in left tail).
  • For a right-tailed test, P (Area in right
    tail).
  • For a two-tailed test, P 2(Area in tail of test
    statistic).
  • Make a decision to reject or fail to reject the
    null hypothesis.
  • Interpret the decision in the context of the
    original claim.

Reject H0 if P-value is less than or equal to ?.
Otherwise, fail to reject H0.
46
Example Hypothesis Testing Using P-values
  • In an advertisement, a pizza shop claims that its
    mean delivery time is less than 30 minutes. A
    random selection of 36 delivery times has a
    sample mean of 28.5 minutes and a standard
    deviation of 3.5 minutes. Is there enough
    evidence to support the claim at ? 0.01? Use a
    P-value.

47
Solution Hypothesis Testing Using P-values
  • H0
  • Ha
  • ?
  • Test Statistic
  • P-value

0.01
  • Decision

0.0051 lt 0.01 Reject H0
At the 1 level of significance, you have
sufficient evidence to conclude the mean delivery
time is less than 30 minutes.
48
Example Hypothesis Testing Using P-values
  • You think that the average franchise investment
    information shown in the graph is incorrect, so
    you randomly select 30 franchises and determine
    the necessary investment for each. The sample
    mean investment is 135,000 with astandard
    deviation of 30,000. Is there enough evidence
    to support your claim at ? 0.05? Use a
    P-value.

49
Solution Hypothesis Testing Using P-values
  • H0
  • Ha
  • ?
  • Test Statistic
  • P-value

P 2(0.0655) 0.1310
0.05
  • Decision

0.1310 gt 0.05 Fail to reject H0
At the 5 level of significance, there is not
sufficient evidence to conclude the mean
franchise investment is different from 143,260.
50
Rejection Regions and Critical Values
  • Rejection region (or critical region)
  • The range of values for which the null hypothesis
    is not probable.
  • If a test statistic falls in this region, the
    null hypothesis is rejected.
  • A critical value z0 separates the rejection
    region from the nonrejection region.

51
Rejection Regions and Critical Values
  • Finding Critical Values in a Normal Distribution
  • Specify the level of significance ?.
  • Decide whether the test is left-, right-, or
    two-tailed.
  • Find the critical value(s) z0. If the hypothesis
    test is
  • left-tailed, find the z-score that corresponds to
    an area of ?,
  • right-tailed, find the z-score that corresponds
    to an area of 1 ?,
  • two-tailed, find the z-score that corresponds to
    ½? and 1 ½?.
  • Sketch the standard normal distribution. Draw a
    vertical line at each critical value and shade
    the rejection region(s).

52
Example Finding Critical Values
  • Find the critical value and rejection region for
    a two-tailed test with ? 0.05.

Solution
1 a 0.95
½a 0.025
½a 0.025
z0 1.96
-z0 -1.96
The rejection regions are to the left of -z0
-1.96 and to the right of z0 1.96.
53
Decision Rule Based on Rejection Region
  • To use a rejection region to conduct a hypothesis
    test, calculate the standardized test statistic,
    z. If the standardized test statistic
  • is in the rejection region, then reject H0.
  • is not in the rejection region, then fail to
    reject H0.

54
Using Rejection Regions for a z-Test for a Mean µ
In Words In Symbols
State H0 and Ha.
  1. State the claim mathematically and verbally.
    Identify the null and alternative hypotheses.
  2. Specify the level of significance.
  3. Sketch the sampling distribution.
  4. Determine the critical value(s).
  5. Determine the rejection region(s).

Identify ?.
Use Table 4 in Appendix B.
55
Using Rejection Regions for a z-Test for a Mean µ
In Words In Symbols
  1. Find the standardized test statistic.
  2. Make a decision to reject or fail to reject the
    null hypothesis.
  3. Interpret the decision in the context of the
    original claim.

If z is in the rejection region, reject H0.
Otherwise, fail to reject H0.
56
Example Testing with Rejection Regions
  • Employees in a large accounting firm claim that
    the mean salary of the firms accountants is less
    than that of its competitors, which is 45,000.
    A random sample of 30 of the firms accountants
    has a mean salary of 43,500 with a standard
    deviation of 5200. At a 0.05, test the
    employees claim.

57
Solution Testing with Rejection Regions
  • H0
  • Ha
  • ?
  • Rejection Region
  • Test Statistic

0.05
  • Decision

Fail to reject H0
At the 5 level of significance, there is not
sufficient evidence to support the employees
claim that the mean salary is less than 45,000.
-1.645
-1.58
58
Example Testing with Rejection Regions
  • The U.S. Department of Agriculture reports that
    the mean cost of raising a child from birth to
    age 2 in a rural area is 10,460. You believe
    this value is incorrect, so you select a random
    sample of 900 children (age 2) and find that the
    mean cost is 10,345 with a standard deviation of
    1540. At a 0.05, is there enough evidence to
    conclude that the mean cost is different from
    10,460? (Adapted from U.S. Department of
    Agriculture Center for Nutrition Policy and
    Promotion)

59
Solution Testing with Rejection Regions
  • H0
  • Ha
  • ?
  • Rejection Region
  • Test Statistic

0.05
Reject H0
  • Decision

At the 5 level of significance, you have enough
evidence to conclude the mean cost of raising a
child from birth to age 2 in a rural area is
significantly different from 10,460.
-1.96
1.96
-2.24
60
Section 7.2 Summary
  • Found P-values and used them to test a mean µ
  • Used P-values for a z-test
  • Found critical values and rejection regions in a
    normal distribution
  • Used rejection regions for a z-test

61
Section 7.3
  • Hypothesis Testing for the Mean (Small Samples)

62
Section 7.3 Objectives
  • Find critical values in a t-distribution
  • Use the t-test to test a mean µ
  • Use technology to find P-values and use them with
    a t-test to test a mean µ

63
Finding Critical Values in a t-Distribution
  • Identify the level of significance ?.
  • Identify the degrees of freedom d.f. n 1.
  • Find the critical value(s) using Table 5 in
    Appendix B in the row with n 1 degrees of
    freedom. If the hypothesis test is
  • left-tailed, use One Tail, ? column with a
    negative sign,
  • right-tailed, use One Tail, ? column with a
    positive sign,
  • two-tailed, use Two Tails, ? column with a
    negative and a positive sign.

64
Example Finding Critical Values for t
  • Find the critical value t0 for a left-tailed test
    given? 0.05 and n 21.
  • Solution
  • The degrees of freedom are d.f. n 1 21 1
    20.
  • Look at a 0.05 in the One Tail, ? column.
  • Because the test is left-tailed, the critical
    value is negative.

65
Example Finding Critical Values for t
  • Find the critical values t0 and -t0 for a
    two-tailed test given ? 0.05 and n 26.
  • Solution
  • The degrees of freedom are d.f. n 1 26 1
    25.
  • Look at a 0.05 in the Two Tail, ? column.
  • Because the test is two-tailed, one critical
    value is negative and one is positive.

66
t-Test for a Mean µ (n lt 30, ? Unknown)
  • t-Test for a Mean
  • A statistical test for a population mean.
  • The t-test can be used when the population is
    normal or nearly normal, ? is unknown, and n lt
    30.
  • The test statistic is the sample mean
  • The standardized test statistic is t.
  • The degrees of freedom are d.f. n 1.

67
Using the t-Test for a Mean µ(Small Sample)
In Words In Symbols
  1. State the claim mathematically and verbally.
    Identify the null and alternative hypotheses.
  2. Specify the level of significance.
  3. Identify the degrees of freedom and sketch the
    sampling distribution.
  4. Determine any critical value(s).

State H0 and Ha.
Identify ?.
d.f. n 1.
Use Table 5 in Appendix B.
68
Using the t-Test for a Mean µ(Small Sample)
In Words In Symbols
  1. Determine any rejection region(s).
  2. Find the standardized test statistic.
  3. Make a decision to reject or fail to reject the
    null hypothesis.
  4. Interpret the decision in the context of the
    original claim.

If t is in the rejection region, reject H0.
Otherwise, fail to reject H0.
69
Example Testing µ with a Small Sample
  • A used car dealer says that the mean price of a
    2005 Honda Pilot LX is at least 23,900. You
    suspect this claim is incorrect and find that a
    random sample of 14 similar vehicles has a mean
    price of 23,000 and a standard deviation of
    1113. Is there enough evidence to reject the
    dealers claim at a 0.05? Assume the population
    is normally distributed. (Adapted from Kelley
    Blue Book)

70
Solution Testing µ with a Small Sample
  • H0
  • Ha
  • a
  • df
  • Rejection Region
  • Test Statistic
  • Decision

0.05
Reject H0
14 1 13
At the 0.05 level of significance, there is
enough evidence to reject the claim that the mean
price of a 2005 Honda Pilot LX is at least 23,900
-1.771
-3.026
71
Example Testing µ with a Small Sample
  • An industrial company claims that the mean pH
    level of the water in a nearby river is 6.8. You
    randomly select 19 water samples and measure the
    pH of each. The sample mean and standard
    deviation are 6.7 and 0.24, respectively. Is
    there enough evidence to reject the companys
    claim at a 0.05? Assume the population is
    normally distributed.

72
Solution Testing µ with a Small Sample
  • H0
  • Ha
  • a
  • df
  • Rejection Region
  • Test Statistic
  • Decision

0.05
Fail to reject H0
19 1 18
At the 0.05 level of significance, there is not
enough evidence to reject the claim that the mean
pH is 6.8.
-2.101
2.101
-1.816
73
Example Using P-values with t-Tests
  • The American Automobile Association claims that
    the mean daily meal cost for a family of four
    traveling on vacation in Florida is 132. A
    random sample of 11 such families has a mean
    daily meal cost of 141 with a standard deviation
    of 20. Is there enough evidence to reject the
    claim at a 0.10? Assume the population is
    normally distributed. (Adapted from American
    Automobile Association)

74
Solution Using P-values with t-Tests
  • H0
  • Ha

TI-83/84set up
Calculate
Draw
  • Decision

0.1664 gt 0.10
Fail to reject H0. At the 0.10 level of
significance, there is not enough evidence to
reject the claim that the mean daily meal cost
for a family of four traveling on vacation in
Florida is 132.
75
Section 7.3 Summary
  • Found critical values in a t-distribution
  • Used the t-test to test a mean µ
  • Used technology to find P-values and used them
    with a t-test to test a mean µ

76
Section 7.4
  • Hypothesis Testing for Proportions

77
Section 7.4 Objectives
  • Use the z-test to test a population proportion p

78
z-Test for a Population Proportion
  • z-Test for a Population Proportion
  • A statistical test for a population proportion.
  • Can be used when a binomial distribution is given
    such that np ? 5 and nq ? 5.
  • The test statistic is the sample proportion .
  • The standardized test statistic is z.

79
Using a z-Test for a Proportion p
Verify that np 5 and nq 5
In Words In Symbols
  1. State the claim mathematically and verbally.
    Identify the null and alternative hypotheses.
  2. Specify the level of significance.
  3. Sketch the sampling distribution.
  4. Determine any critical value(s).

State H0 and Ha.
Identify ?.
Use Table 5 in Appendix B.
80
Using a z-Test for a Proportion p
In Words In Symbols
  1. Determine any rejection region(s).
  2. Find the standardized test statistic.
  3. Make a decision to reject or fail to reject the
    null hypothesis.
  4. Interpret the decision in the context of the
    original claim.

If z is in the rejection region, reject H0.
Otherwise, fail to reject H0.
81
Example Hypothesis Test for Proportions
  • Zogby International claims that 45 of people in
    the United States support making cigarettes
    illegal within the next 5 to 10 years. You decide
    to test this claim and ask a random sample of 200
    people in the United States whether they support
    making cigarettes illegal within the next 5 to 10
    years. Of the 200 people, 49 support this law.
    At a 0.05 is there enough evidence to reject
    the claim?
  • Solution
  • Verify that np 5 and nq 5.

np 200(0.45) 90 and nq 200(0.55) 110
82
Solution Hypothesis Test for Proportions
  • H0 (claim)
  • Ha
  • ?
  • Rejection Region
  • Test Statistic

0.05
Fail to reject H0
  • Decision

At the 5 level of significance, there is not
enough evidence to reject the claim that 45 of
people in the U.S. support making cigarettes
illegal within the next 5 to 10 years.
-1.96
1.96
1.14
83
Example Hypothesis Test for Proportions
  • The Pew Research Center claims that more than 55
    of U.S. adults regularly watch their local
    television news. You decide to test this claim
    and ask a random sample of 425 adults in the
    United States whether they regularly watch their
    local television news. Of the 425 adults, 255
    respond yes. At a 0.05 is there enough evidence
    to support the claim?
  • Solution
  • Verify that np 5 and nq 5.

np 425(0.55) 234 and nq 425 (0.45) 191
84
Solution Hypothesis Test for Proportions
  • H0
  • Ha
  • ?
  • Rejection Region
  • Test Statistic

0.05
Reject H0
  • Decision

At the 5 level of significance, there is enough
evidence to support the claim that more than 55
of U.S. adults regularly watch their local
television news.
1.645
2.07
85
Section 7.4 Summary
  • Used the z-test to test a population proportion p
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