Transcript Notes

CHAPTER 23
THE MORE T-DISTRIBUTION & SIGNIFICANCE
TESTING FOR QUANTITATIVE DATA
HYPOTHESIS TESTING FOR MEANS
(QUANTITATIVE DATA)
•
THE SAME 5 STEPS NO MATTER
THE DATA TYPE:
• Common Steps to all Significance Tests:
1) State Ho and Ha.
2) Specify significance level, .
3) Identify correct test and conditions.
4) Calculate the value of the test statistic
5) Find the P-value for the observed data
(If the P-value is less than or = to , the
test
result is “statistically significant at level .)
6) Answer the question in context.
WRITING HYPOTHESES
• To test the hypothesis: Ho:  = o and
•
Ha:
 > o
•
Ha:
 < o
•
Ha:
  o
• Calculate the test statistics t and the p value.
• These have the same meanings as they did for
proportions. We make the same conclusions based
on p-values and alpha.
CONDITIONS:
The conditions for hypothesis testing are the same as
they were for confidence intervals when the data is
quantitative.
DO THE MATH:
•
WRITING YOUR CONCLUSION:
• Remember your two possible conclusions:
• If p value < α,
•
With a p-value of ___ < α at ____, we can
reject the null & can support _____(the
alternative in context).
• If p-value > α,
•
With a p-value of ___ > α at ____, we fail
to reject the null and we can not support
that _____ (the alternative in context).
EXAMPLE 1
• Last year the number of false fire alarms in a large
city averaged 10.4 a day. In an effort to reduce this
number, the fire department conducted a safety
program in the city’s schools. Six months after
completion of the program, a sample of 21 days
had a mean of 8.1 false alarms and a standard
deviation of 3.4. Does it appear that the fire
department’s program is successful?
•
EXAMPLE 2
• A new blood pressure drug is advertised to reduce
a patient’s blood pressure an average of 10 units
after a week of medication. Blood pressure
reductions were recorded for 37 patients after
treatment with the drug for 1 week. The patients
had a mean reduction in blood pressure of 8.7 units
with a standard deviation of 5.1 units. Is there
evidence to dispute the advertised claim from the
drug’s manufacturer?
•
EXAMPLE 3
• The mean yield of corn in the United States is about
120 bushels per acre. A survey of 50 farmers this
year gives a sample mean yield of x-bar = 123.6
bushels per acre with a standard deviation of sx= 10
bushels per acre. We want to know whether this is
good evidence that the national mean this year is
not 120 bushels per acre. Assume that the farmers
surveyed are an SRS from the population of all
commercial corn growers.
• Are you convinced that the population mean is not
120 bushels per acre?
EXAMPLE 4
• A pharmaceutical manufacturer does a chemical analysis to
check the potency of its products. The standard release
potency for cephalothin crystals is 910 ppm. An SRS of 16 lots
gives the following potency data:
•
897
914
913
906
916
918
905
921
918
906
895
893
•
908
906
907
901
•
• You want to know if the cephalothin crystals have lost
potency during shipping and storage.
EXAMPLE 5
• The manufacturer of an over-the-counter pain reliever claims
that the product brings pain relief to headache sufferers in less
than 3.5 minutes, on average. In order to be able to make this
claim in its television advertisements, the manufacturer was
required by a particular television network to present statistical
evidence in support of the claim. The manufacturer reported
that for a random sample of 50 headache sufferers, the mean
relief time was 3.3 minutes with a standard deviation of 1.1
minutes.
• Do the data support the manufacturers claim?
• Test using a significance level of 5%.