1. WARM – UP
Are twin births on the rise in the United States? In % of all births produced twins. In 2009 Data from an SRS of 469 mothers in a large city found that 4.05% resulted in sets of twins being born. Test the appropriate hypothesis and state your conclusions and assumptions.
p = The true proportion of twins births in the United States.
One Proportion
z – Test
H0: p = 0.03 Ha: p > 0.03
SRS – The data was collected randomly
Appr. Normal: 469 · (0.03) ≥ AND · (1 – 0.03) ≥ 10
Population of US births is ≥ 10 · (469)
Since the P-Value is NOT less than α = we Fail to REJECT H0 . There is no evidence to suggest that Twin births are on the rise in the US.

2. Since the P-value = is
high, we fail to reject the null
hypothesis. There is little
evidence of an increase in
dropout rate from 10.9%.
Since the P-value = is
low, we reject the null
hypothesis. There is strong
evidence that the trees in
Hopkins forest have a greater
proportion of acid rain damage
than the 15% reported for the
Northeast.
Since the P-value = is
low, we reject the null
hypothesis. There is evidence
that the proportion of lost
luggage returned the next day is
lower than the 90% claimed by
the airline.
Since the P-value = is
fairly high, we fail to reject the
null hypothesis. There is little
evidence that more than 40% of
the public recognizes the
product.
Don’t run commercials during
the Super Bowl!

3. Chapter 21 – More about Tests
H0 = NO CHANGE in Population, No effect, THE NORM, or THE EXPECTATION. H0: p = #
ONE-Tailed Test – Ha: p > # or Ha: p < #
TWO-Tailed Test : Ha: p ≠ #

4. Chapter 21 – More about Tests
The alpha level, α =0.05,is also called the significance level.
Common alpha levels are 0.10, 0.05, and 0.01.
When we reject the null hypothesis, we say that the test is “significant at that level.”
What can you say if the P-value does not fall below ?
You should say that “The data have failed to provide sufficient evidence to reject the null hypothesis.”
NEVER “accept the null hypothesis”. ONLY “Fail to Reject the null hypothesis.”

5. (β = probability of committing a Type II Error.)
Chapter 21
STATISTICAL ERRORS
If we Reject H0 when in fact H0 is TRUE this is a
TYPE I ERROR = (false positive).
(α = probability of committing a Type I Error.)
If we Fail to Reject H0 when in fact H0 is FALSE (Ha is True) this is a TYPE II ERROR = (false negative).
(β = probability of committing a Type II Error.)
Decision based on sample
Reject H0
Fail to Reject H0
H0 is True
H0 is False
Type I Error
Correct Decision
Type II Error
Correct Decision

6. Homework: Page 492: (#11-14: a-d only),
(#17-18: a-c only)

7. In each example List the Hypothesis and then Describe the Type I and Type II Error. Page 492
11. In 2003 the Dept. of Commerce reported that 68.2% of American families own homes. In order to encourage home ownership the city offers a plan of tax breaks for first time home buyers. Since the plan cost the city tax revenues, they will continue using it only if there is strong evidence that the rate of home ownership is increasing.
H0: Home ownership remains Unchanged Not rising.
Ha: Home ownership is Increasing.
TYPE I ERROR = The city feels that home ownership is on the rise but in fact the tax breaks are not helping. The city forgoes tax revenues for nothing.
TYPE II ERROR = The city feels homeownership remains unchanged (68.2%), but it is increasing. They may retract the tax breaks feeling they are useless.

8. In each example List the Hypothesis and then Describe the Type I and Type II Error.
12. Recently a group of doctors devised a quick test to test for the Alzheimer in the population of senior citizens. A patient that tested positive would then go through a more expensive and time consuming battery of tests and medical diagnosis.
H0: The Patient does not have Alzheimer (Healthy)
Ha: The Patient has Alzheimer
TYPE I ERROR = The Patient is diagnosed with Alzheimer but does NOT have the disease. The Patient waste time and money… and stress. FALSE POSITIVE
TYPE II ERROR = The patient is diagnosed as healthy when they do have Alzheimer. The patient does not receive the beneficial treatment. FALSE NEGATIVE

9. In each example List the Hypothesis and then Describe the Type I and Type II Error.
13. Clean Air standards require that vehicle exhausts not exceed specified limits. Many states require annual test. State Regulators sample shops all the time. They will revoke the shop’s license if they find that they are certifying vehicles that do not meet the standards.
H0: The Shop is certifying cars that are meeting the standards.
Ha: The Shop is certifying cars that DO NOT meet the standards.
TYPE I ERROR = The state regulator decides that the shop is not meeting the standards when they really are. The shop is fined and license revoked.
TYPE II ERROR = The state regulators decide that the shop is following standards when it is NOT. Consequently the air is being polluted.

10. Homework: Page 492: (#11-14: a-d only),
(#17-18: a-c only)

11. Homework: Page 492: (#11-14: a-d only),
(#17-18: a-c only)

12. Homework: Page 492: (#11-14: a-d only),
(#17-18: a-c only)

14. Back to the Basics…
Are twin births on the rise in the United States? In % of all births produced twins. In 2005 Data from an SRS of 469 mothers in a large city found that 19 sets of twins were born to 469 mothers. Test the appropriate hypothesis and state your conclusions and assumptions.
Because our sample size is 469 we get a Sampling Distribution of…
P-value =
N(0.03, )
Definintion of P-value: The Probability of obtaining this statistic, p = 19/469 = , given that the Null hypothesis of μ = 0.03 is TRUE.

15. Back to the Basics…
What happens if you increase the sample size? Lets say that we obtain a sample of 2000 births of which 81 result in twins.
Because our sample size is 2000 we get a Sampling Distribution of…
P-value =
N(0.03, )
Definintion of P-value: The Probability of obtaining this statistic, p = 81/2000 = , given that the Null hypothesis of μ = 0.03 is TRUE.