Chapter 8 Hypothesis Testing Notes, Study notes of Statistics

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Chapter 8 Hypothesis Testing Notes

In statistics, a hypothesis is a claim or statement about a property of a population.

A hypothesis test (or test of significance) is a standard mathematical procedure for testing a claim about a property of a population.

If, under a given assumption, the probability of a particular observed event is exceptionally small, we conclude that the assumption is probably not correct.

Example: Suppose we conduct an experiment with 100 couples who want to have baby girls, and

they all follow the Gender Choice “easy-to-use in-home system” described in the pink package. For the purpose of testing the claim of an increased likelihood for girls, we will assume that Gender

Choice has no effect.

Using common sense and no formal statistical methods, what should we conclude about the assumption of no effect from Gender Choice if 100 couples using Gender Choice have 100 babies

consisting of a) 52 girls?; b) 97 girls?

a) We normally expect around 50 girls in 100 births. The result of 52 girls is close to 50, so we should not conclude that the Gender Choice product is effective. If the 100 couples used no special method of gender selection, the result of 52 girls could easily occur by chance. The assumption of no effect from Gender Choice appears to be correct. There isn’t sufficient evidence to say that Gender Choice is effective.

b) The result of 97 girls in 100 births is extremely unlikely to occur by chance. We could explain the occurrence of 97 girls in one of two ways: Either an extremely rare event has occurred by chance, or Gender Choice is effective. The extremely low probability of getting 97 girls is strong evidence against the assumption that Gender Choice has no effect. It does appear to be effective.

Key Components of a Hypothesis Test

First Goal: Given a claim, identify the null hypothesis and the alternative hypothesis, and express them both in symbolic form.

 The null hypothesis (denoted by H 0 ) is a statement that the value of a population parameter (such as proportion p , mean  , or standard deviation  ) is equal to some claimed value. H 0 : p = (NUMBER) H 0 :  = (NUMBER) H 0 :  = (NUMBER)  Any decision is always made about the null hypothesis:

Either reject H 0

or fail to reject H 0

 The alternative hypothesis (denoted by H 1

or H a

or H A

) is the statement that the parameter has a value that somehow differs from the null hypothesis.  The symbolic form of the alternative hypothesis must use one of these symbols:  , <, >. H A

: p  or < or > ( Same NUMBER)

H A

:   or < or > (Same NUMBER)

H A

:   or < or > (Same NUMBER)

Example: Identify the Null and Alternative Hypothesis. Use the given claims to express the

corresponding null and alternative hypotheses in symbolic form. ℎ 0 represents the given value, ℎ𝑎 should be a compliment of it

a) The proportion of drivers who admit to running red lights is greater than 0.5.

H 0 : p = 0.5.

H a : p > 0.5,

and we let p be the true proportion of drivers who admit to running red lights

b) The mean height of professional basketball players is at most 7 ft.

b) H 0

: μ = 7 H a

: μ < 7

and we let μ be the true mean height of professional basketball players

c) The standard deviation of IQ scores of actors is equal to 15.

H 0

:  = 15 H a

:   15

Where  is the true standard deviation of IQ scores of actors

Second Goal:

Given a claim and sample data, calculate the value of the test statistic.

The test statistic is a value used in making a decision about the null hypothesis, and is found by converting the sample statistic to a score with the assumption that the null hypothesis is true.

Test Statistic - Formulas

Very similar to critical values from the last unit. We just account for less than and greater than with one or two tails.

We always test the null hypothesis. The initial conclusion will always be one of the following:

1. Reject the null hypothesis. Reject H 0

if the test statistic falls within the critical region.

2. Fail to reject the null hypothesis. Fail to reject H 0

if the test statistic does not fall within the

critical region.

Example: Given the following information find the p-value

1. The test statistic is z=.52 and it is right tailed. 2. Test statistic is left tailed and z=-1.

3. The test statistic is 1.95 and is two tailed.

Identify the null hypothesis the alternative hypothesis, test statistic, p-value and conclusion about the null hypothesis and final conclusion that addresses the original claim

1. According to recent poll 53% of Americans would vote for the incumbent president. If a random

sample of 11 people results in 45% who would vote for the incumbent, test the claim the actual

percentage is 53%. Us a .10 significance level

ℎ 0 𝑝 = .53 p-value: Using a z of 1.6 ∝=.

ℎ𝑎 𝑝 ≠ 53

Test Statistic 𝑧 =

.45−.

√(.53)(.47) 100

= 1.

Critical value at 90% is 1.645, fail to reject null hypothesis. It falls within the critical value

∝> 𝑝̂ do not reject null hypothesis

∝< 𝑝̂ reje

2. Previously, an organization reported that teenagers spent 4.5 hours per week, on average, on the phone. The organization thinks that, currently, the mean is higher. Fifteen randomly chosen teenagers were asked how many hours per week they spend on the phone. The sample mean was 4.75 hours with a sample standard deviation of 2.0. Conduct a hypothesis test with 9 5 % confidence level

4.75−4. 2 √

= 0.484 p-value 0.314 Falls within the critical value

We will not reject this null hypothesis

Prob/Stat:

I. Identifying Ho and HA. State the null and Alternative Hypotheses in symbolic notation and identify the

claim.

1. A university claims that the proportion of its students who graduate in four years is more than 82%.

Ho :

HA :

2. A water faucet manufacturer claims that the mean flow rate of a certain type of faucet is less than 2.

gallons per minutes.

Ho :

HA :

3. A television manufacturer claims that the standard deviation of the life of a certain type of television is

3 years.

Ho :

HA :

II. Sketch the normal distribution , label the areas for each significance level, shade the “tails” and find

and label the critical values.

4. (Two-tailed test) HA : p≠ 0.5, 𝛼 = 0.

5. (Left tailed test) HA : 𝜇 < 12 feet, 𝛼 = 0.

6. (Right-tailed test) HA : p > 0.5, 𝛼 = 0.

Hypothesis Testing Worksheet

1. For the following pairs, indicate which aren’t legitimate hypotheses and explain why.

a) Ho : 𝑝 ≠ 0.4 ∶ HA: 𝑝̂ > 0.

b) Ho : 𝑝̂ = 0.16 ∶ HA: 𝑝̂ > 0.

c) Ho : 𝜇 = 22 ∶ HA:𝜇 > 24

For each of the following, a) draw and shade the curve

b) calculate the p-value of the given test statistic

5) Right-tailed test z = 2.

6) Left-tail test z = -1.

7) Two-tail test z = 1.

8) A newspaper article headline reads “One in Five Believe Path to Riches Is the Lottery”. A survey was

done to test the claim that 20% of adult Americans believe that the lottery is the path to riches. The

hypothesis test of Ho: p = 0.2 versus p > 0.2 resulted in z = 0.79 for a right tailed test. Calculate the p-

value and write the correct conclusion in context.

9) A researcher claims that less than 30% of adults are allergic to weeds. IN a random sample of 86 adults,

17 said they have such an allergy. At a significance level of 𝛼 = 0.05, is there enough evidence to

support the researcher’s claim.

10) Mendel”s Genetic Experiments. When Gregor Mendel conducted his famous hybridization experiment

with peas, one such experiment in offspring consisting of 428 peas with green pods and 152 peas with

yellow pods. According to his theory, ¼ of the offspring peas should have yellow pods. Use a 0.

significance level to test the claim that the proportion of peas with yellow pods is equal to ¼.

Probability Distribution Review