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7.4 ESTIMATING 1  2 AND P1
 P2
Independent Samples and
              Dependent Samples
   In this section, we will use samples from two
    populations to create confidence intervals for
    the difference between population parameters.
     we need to have a sample from each population
     Samples may be independent or dependent
      according to how they are selected
Independent Samples and
                Dependent Samples
   Two samples are independent is sample data
    drawn from one population are completely
    unrelated to the selection of sample data from the
    other population.
       Examples
         Sample 1: test scores for 35 statistics students
          Sample 2: test scores for 42 biology students
         Sample 1: heights of 27 adult females
          Sample 2: heights of 27 adult males
         Sample 1: the SAT scores for 35 high school students who
          did not take an SAT preparation course
          Sample 2: the SAT scores for 40 high school students who
        did take an SAT preparation course
Independent Samples and
                Dependent Samples
   Two samples are dependent if each data value in
    one sample can be paired with a corresponding
    data value in the other sample.
       Examples
         Sample 1: resting heart rates of 35 individuals before
          drinking coffee
          Sample 2: resting heart rates of the same individuals after
          drinking two cups of coffee
         Sample 1: midterm exam scores of 14 chemistry students
          Sample 2: final exam scores of the same 14 chemistry
        students
         Sample 1: the fuel mileage of 10 cars
          Sample 2: the fuel mileage of the same 10 cars using a fuel
          additive
Independent Samples and
            Dependent Samples
   Dependent samples and data pairs occur very
    naturally in before and after situations in
    which the same object or item is measured
    twice.
   Independent samples occur very naturally
    when we draw two random samples, one from
    the first population and one from the second
    population.
   All the examples of this section will involve
    independent random samples.
Confidence Intervals for the
difference between two population
parameters
   There are several types of confidence intervals
    for the difference between two population
    parameters
     Confidence Intervals for 1  2 (1 and 2
      known)
     Confidence Intervals for 1  2 (1 and 2 Are
      Unknown)
     Confidence Intervals for 1  2 (1 = 2)

     Confidence Intervals for p1  p2
Confidence Intervals for 1  2
          (1 and 2 known)
How to Interpret Confidence
    Intervals for Differences
Confidence Intervals for 1  2
          (1 and 2 known)
Confidence Intervals for 1  2
          (1 and 2 known)
Example 8                                 Page 375
Confidence interval for 1  2, 1 and 2 known
   In the summer of 1988, Yellowstone National Park had some major fires
    that destroyed large tracts of old timber near many famous trout streams.
    Fishermen were concerned about the long-term effects of the fires on
    these streams. However, biologists claimed that the new meadows that
    would spring up under dead trees would produce a lot more insects, which
    would in turn mean better fishing in the years ahead. Guide services
    registered with the park provided data about the daily catch for fishermen
    over many years. Ranger checks on the streams also provided data about
    the daily number of fish caught by fishermen. Yellowstone Today (a
    national park publication) indicates that the biologists claim is basically
    correct and that Yellowstone anglers are delighted by their average
    increased catch. Suppose you are a biologist studying fishing data from
    Yellowstone streams before and after the fire. Fishing reports include the
    number of trout caught per day per fisherman.
   A random sample of n1 = 167 reports from the period before the fire
    showed that the average catch was x1 = 5.2 trout per day. Assume that the
    standard deviation of daily catch per fisherman during this period was 1 =
    1.9 . Another random sample of n2 = 125 fishing reports 5 years after the
    fire showed that the average catch per day was x2 = 6.8 trout. Assume that
    the standard deviation during this period was 2 = 2.3.
Example 8                                Page 375
    Confidence interval for 1  2, 1 and 2
    known





Solution:
The population for the first sample is the number of trout caught per day by
fishermen before the fire.
The population for the second sample is the number of trout caught per day
after the fire.
Both samples were random samples taken in their respective time periods.
There was no effort to pair individual data values. Therefore, the samples
can be thought of as independent samples.
A normal distribution is appropriate for the x1  x2 distribution because
sample sizes are sufficiently large and we know both 1 and 2.
Example 8                 Page 375
Confidence interval for 1  2, 1 and 2
known
Example 8                  Page 375
     Confidence interval for 1  2, 1 and 2
     known
c)   Interpretation What is the meaning of the
     confidence interval computed in part (b)?

Solution:
Since the confidence interval contains only negative
values, we are 95% sure that 1  2 < 0. This
means we are 95% sure that 1 < 2 .
Confidence Intervals for 1  2
(1 and 2 Are Unknown)
Confidence Intervals for 1  2
(1 and 2 Are Unknown)
Confidence Intervals for 1  2
(1 and 2 Are Unknown)
Example 9                 Page 377
Confidence interval for 1  2, 1 and 2
unknown
Alexander Borbely is a professor at the Medical School of the University of Zurich,
where he is director of the Sleep Laboratory. Dr. Borbely and his colleagues are
experts on sleep, dreams, and sleep disorders. In his book Secrets of Sleep, Dr.
Borbely discusses brain waves, which are measured in hertz, the number of
oscillations per second. Rapid brain waves (wakefulness) are in the range of 16
to 25 hertz. Slow brain waves (sleep) are in the range of 4 to 8 hertz. During
normal sleep, a person goes through several cycles (each cycle is about 90
minutes) of brain waves, from rapid to slow and back to rapid. During deep sleep,
brain waves are at their slowest. In his book, Professor Borbely comments that
alcohol is a poor sleep aid. In one study, a number of subjects were given 1/2 liter
of red wine before they went to sleep. The subjects fell asleep quickly but did not
remain asleep the entire night. Toward morning, between 4 and 6 A.M., they
tended to wake up and have trouble going back to sleep.
Suppose that a random sample of 29 college students was randomly divided into
two groups. The first group of n1 = 15 people was given 1/2 liter of red wine
before going to sleep. The second group of n2 = 14 people was given no alcohol
before going to sleep. Everyone in both groups went to sleep at 11 P.M. The
average brain wave activity (4 to 6 A.M.) was determined for each individual in
the groups. Assume the average brain wave distribution in each group is
moundshaped and symmetric.
Example 9                 Page 377
Confidence interval for 1  2, 1 and 2
unknown
Example 9                 Page 377
Confidence interval for 1  2, 1 and 2
unknown
Example 9                 Page 377
Confidence interval for 1  2, 1 and 2
unknown
Example 9                 Page 377
Confidence interval for 1  2, 1 and 2
unknown
 c)  Interpretation What is the meaning of the
     confidence interval you computed in part (b)?
 Solution
 We are 90% confident that the interval between 11.8
 and 14.3 hertz is one that contains the difference 1 
 2.
 Since the confidence interval from 11.8 to 14.3
 contains only positive values, we could express this
 by saying that we are 90% confident that 1  2 is
 positive.
 This means that 1  2 > 0. Thus, we are 90%
 confident
 1 > 2
Assignment
   Page 384
   #1, 2, 4  6, 7, 11, 23, 31
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7.4

  • 1. 7.4 ESTIMATING 1 2 AND P1 P2
  • 2. Independent Samples and Dependent Samples In this section, we will use samples from two populations to create confidence intervals for the difference between population parameters. we need to have a sample from each population Samples may be independent or dependent according to how they are selected
  • 3. Independent Samples and Dependent Samples Two samples are independent is sample data drawn from one population are completely unrelated to the selection of sample data from the other population. Examples Sample 1: test scores for 35 statistics students Sample 2: test scores for 42 biology students Sample 1: heights of 27 adult females Sample 2: heights of 27 adult males Sample 1: the SAT scores for 35 high school students who did not take an SAT preparation course Sample 2: the SAT scores for 40 high school students who did take an SAT preparation course
  • 4. Independent Samples and Dependent Samples Two samples are dependent if each data value in one sample can be paired with a corresponding data value in the other sample. Examples Sample 1: resting heart rates of 35 individuals before drinking coffee Sample 2: resting heart rates of the same individuals after drinking two cups of coffee Sample 1: midterm exam scores of 14 chemistry students Sample 2: final exam scores of the same 14 chemistry students Sample 1: the fuel mileage of 10 cars Sample 2: the fuel mileage of the same 10 cars using a fuel additive
  • 5. Independent Samples and Dependent Samples Dependent samples and data pairs occur very naturally in before and after situations in which the same object or item is measured twice. Independent samples occur very naturally when we draw two random samples, one from the first population and one from the second population. All the examples of this section will involve independent random samples.
  • 6. Confidence Intervals for the difference between two population parameters There are several types of confidence intervals for the difference between two population parameters Confidence Intervals for 1 2 (1 and 2 known) Confidence Intervals for 1 2 (1 and 2 Are Unknown) Confidence Intervals for 1 2 (1 = 2) Confidence Intervals for p1 p2
  • 7. Confidence Intervals for 1 2 (1 and 2 known)
  • 8. How to Interpret Confidence Intervals for Differences
  • 9. Confidence Intervals for 1 2 (1 and 2 known)
  • 10. Confidence Intervals for 1 2 (1 and 2 known)
  • 11. Example 8 Page 375 Confidence interval for 1 2, 1 and 2 known In the summer of 1988, Yellowstone National Park had some major fires that destroyed large tracts of old timber near many famous trout streams. Fishermen were concerned about the long-term effects of the fires on these streams. However, biologists claimed that the new meadows that would spring up under dead trees would produce a lot more insects, which would in turn mean better fishing in the years ahead. Guide services registered with the park provided data about the daily catch for fishermen over many years. Ranger checks on the streams also provided data about the daily number of fish caught by fishermen. Yellowstone Today (a national park publication) indicates that the biologists claim is basically correct and that Yellowstone anglers are delighted by their average increased catch. Suppose you are a biologist studying fishing data from Yellowstone streams before and after the fire. Fishing reports include the number of trout caught per day per fisherman. A random sample of n1 = 167 reports from the period before the fire showed that the average catch was x1 = 5.2 trout per day. Assume that the standard deviation of daily catch per fisherman during this period was 1 = 1.9 . Another random sample of n2 = 125 fishing reports 5 years after the fire showed that the average catch per day was x2 = 6.8 trout. Assume that the standard deviation during this period was 2 = 2.3.
  • 12. Example 8 Page 375 Confidence interval for 1 2, 1 and 2 known Solution: The population for the first sample is the number of trout caught per day by fishermen before the fire. The population for the second sample is the number of trout caught per day after the fire. Both samples were random samples taken in their respective time periods. There was no effort to pair individual data values. Therefore, the samples can be thought of as independent samples. A normal distribution is appropriate for the x1 x2 distribution because sample sizes are sufficiently large and we know both 1 and 2.
  • 13. Example 8 Page 375 Confidence interval for 1 2, 1 and 2 known
  • 14. Example 8 Page 375 Confidence interval for 1 2, 1 and 2 known c) Interpretation What is the meaning of the confidence interval computed in part (b)? Solution: Since the confidence interval contains only negative values, we are 95% sure that 1 2 < 0. This means we are 95% sure that 1 < 2 .
  • 15. Confidence Intervals for 1 2 (1 and 2 Are Unknown)
  • 16. Confidence Intervals for 1 2 (1 and 2 Are Unknown)
  • 17. Confidence Intervals for 1 2 (1 and 2 Are Unknown)
  • 18. Example 9 Page 377 Confidence interval for 1 2, 1 and 2 unknown Alexander Borbely is a professor at the Medical School of the University of Zurich, where he is director of the Sleep Laboratory. Dr. Borbely and his colleagues are experts on sleep, dreams, and sleep disorders. In his book Secrets of Sleep, Dr. Borbely discusses brain waves, which are measured in hertz, the number of oscillations per second. Rapid brain waves (wakefulness) are in the range of 16 to 25 hertz. Slow brain waves (sleep) are in the range of 4 to 8 hertz. During normal sleep, a person goes through several cycles (each cycle is about 90 minutes) of brain waves, from rapid to slow and back to rapid. During deep sleep, brain waves are at their slowest. In his book, Professor Borbely comments that alcohol is a poor sleep aid. In one study, a number of subjects were given 1/2 liter of red wine before they went to sleep. The subjects fell asleep quickly but did not remain asleep the entire night. Toward morning, between 4 and 6 A.M., they tended to wake up and have trouble going back to sleep. Suppose that a random sample of 29 college students was randomly divided into two groups. The first group of n1 = 15 people was given 1/2 liter of red wine before going to sleep. The second group of n2 = 14 people was given no alcohol before going to sleep. Everyone in both groups went to sleep at 11 P.M. The average brain wave activity (4 to 6 A.M.) was determined for each individual in the groups. Assume the average brain wave distribution in each group is moundshaped and symmetric.
  • 19. Example 9 Page 377 Confidence interval for 1 2, 1 and 2 unknown
  • 20. Example 9 Page 377 Confidence interval for 1 2, 1 and 2 unknown
  • 21. Example 9 Page 377 Confidence interval for 1 2, 1 and 2 unknown
  • 22. Example 9 Page 377 Confidence interval for 1 2, 1 and 2 unknown c) Interpretation What is the meaning of the confidence interval you computed in part (b)? Solution We are 90% confident that the interval between 11.8 and 14.3 hertz is one that contains the difference 1 2. Since the confidence interval from 11.8 to 14.3 contains only positive values, we could express this by saying that we are 90% confident that 1 2 is positive. This means that 1 2 > 0. Thus, we are 90% confident 1 > 2
  • 23. Assignment Page 384 #1, 2, 4 6, 7, 11, 23, 31