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Sampling Distribution of the Difference Between Two statistics

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Title: Sampling Distribution of the Difference Between Two statistics


1
Sampling Distribution of the Difference Between
Two statistics
2
5.4 Sampling Distribution of the Difference
Between Two sample means
  • Independent random samples of size n1 and n2 are
    selected from two populations that have means ?1
    and ?2 and standard deviations ?1 and ?1,
    respectively. If n1 and n2 are each larger than
    30, then
  • is approximately normally distributed.
  • is centered at ?1-?2
  • has a standard deviation of

3
Note
  • If the two populations are normally distributed,
    then the sample distribution of is
    also normally distributed regardless of the
    sample size

4
Sampling Distribution of the Difference Between
Two Means
5
Example 5.4
  • The starting salaries of MBA students from two
    universities (MSU and UM) are 62,000 (stand.dev.
    14,500), and 60,000 (stand. dev. 18,300).
  • What is the probability that a sample mean of MSU
    students will exceed the sample mean of UM
    students? (nMSU 50 nUM 60)

6
Example 5.4 Solution
  • We need to determine

m1 - m2 62,000 - 60,000 2,000
1 - .2611
7
Sampling Distribution of Difference Between Two
Proportions
  • If n1 and n2 are sufficient large, then the
    sampling distribution of P1-P2
  • is approximately normally distributed.
  • is centered at ?1-?2.
  • has a standard deviation of

8
Chapter 7
Confidence Intervals
9
Estimation
  • There are 2 types of estimation in statistics
    point estimation and interval estimation.

10
Confidence Intervals (CI)
  • A confidence interval for a population
    parameter is
  • an interval of possible values for the unknown
    parameter.
  • The interval is computed from sample data in such
    a way that we have a high degree of confidence
    that the interval contains the true value of the
    parameter.
  • The degree of confidence, stated as a percent, is
    the confidence level.

11
The form of confidence interval
  • estimate margin of error (ME)
  • Three factors must be made to develop a CI
  • a good point estimator of the parameter
  • The sampling distribution or approximate
    distribution of the point estimate (standard
    deviation of the estimate).
  • The desired confidence level (1- ? )100.

12
7.1 Confidence Interval for population
proportion ?
  • Standard error of the estimate p
  • SE(p)
  • In general , the large sample (1- ?
    )100confidence interval for ? of based on p is
    given by
  • pME p z

13
The critical value for the standard normal
distribution
  • Find z and z such that

14
z ?
The blue area is 1-?
Standard Normal Distn
z
-z
15
Select values of z
  • (1-?) is how confident we want to be that the
    confidence interval WILL contain the parameter of
    interest. Well refer to these as the level of
    confidence.

16
Steps to calculate CI for ?
  • Calculate estimate p and SE(p)
  • Find the critical value z from the Z-table
    corresponding to the level (1-?)
  • ME z SE
  • CIpME

17
Example 7.1
  • To find the proportion of all students who study
    on weekends, survey 200 students and find out 60
    students study on weekends, find out 95
    confidence interval for ?

18
  • (23.65,36.35)

19
Confidence intervals for ? Interpretation
  • The (for example) 95 confidence interval
    procedure has a 0.95probability of working
    (giving an interval containing ?) before the data
    are collected. (Before the data are collected, is
    a random variable .)
  • If samples of the same size are drawn repeatedly
    from a population, and a confidence interval is
    calculated from each sample, then 95 of these
    intervals should contain the population
    proportion

20
Question1
  • How much data do we need to get a confidence
    interval with margin of error B or less?
  • Sample Size Determination for Estimating ?

21
Finding the desired sample size for estimating ?
B
B
B
B
In this case, 0.5 is used in place of p because
this is where is largest. This is
a worst case scenario.
Here, you have to estimate p from a smaller
sample size.use p in the old studies
22
Example 7.1 (continued)
  • The estimate margin of error for the 95
    confidence interval is .0635, find the sample
    size necessary to reduce the margin to .03? How
    about .01?
  • Answer 897, for B0.03

23
Exercise 7.1
  • Of 900 people treated with new drug, 180 showed
    an allergic reaction. Estimate with a 90
    confidence interval the proportion of the
    proportion who will show an allergic reaction.
  • How large a sample is necessary to ensure that
    the margin of error is no greater than .03

24
  • Answer
  • (.178,.222)
  • 482

25
7.2 Confidence interval for ? based on
when ? is known the z-interval.
The standard deviation of the estimate.
An estimate for µ
Depends on how confident you want to be.
26
Margin of Error
Y
  • The margin of error (ME ) is half the width of
    the confidence interval.

27
Steps to calculate CI for ?
  • Calculate estimate and SE( )
  • Find the critical value z from the Table
    corresponding to the level (1-?)
  • ME z SE
  • CI ME

28
Finding the sample size to estimate ?.
  • For a given bound B on the margin of error, the
    sample size

29
Example 7.2
  • Based on a sample of 35 cars of a particular
    model, the fuel tank capacity is calculated for
    each. Based on this data, the sample mean is
    18.99 gallons. The population standard deviation
    is believed to be 3.5. Obtain a 90 confidence
    interval for the mean fuel capacity of this model
    of car.

30
Cont.
  • We are 90 confident that the mean fuel
  • capacity is between 18.01 and 18.96
  • gallons.

31
Exercise 7.2
  • A consumer research group sampled 100 hand-held
    video games, all of the same make and model. The
    sample mean life was 560 hours. Assuming the
    standard deviation is 35 hours, construct 90
    confidence interval estimate of the true mean
    life span of the video games.
  • Is a 95 confidence interval wider or narrower
    than the interval you got?

32
  • Answer
  • (554.24, 565.76)
  • A 95 CI would be wider because the margin of
    error would be multiplied by 1.96 instead of 1.645

33
Exercise 7.3
  • Suppose a 95 confidence interval for µ is (4.2,
    4.8). What is the sample mean? Whats the width
    of this interval? What is the margin of error?
    Standard error?
  • Whats the width of the interval below?

34
  • Answer7.3
  • Sample mean4.5
  • Width of CI0.6
  • ME0.3
  • SE0.153

35
Example7.2(continue)
  • Earlier we obtained a confidence interval
  • for the mean fuel capacity of a certain
  • model of car. In that example, we were
  • given the sample size of 35. This time,
  • suppose that we want to obtain a 90
  • confidence interval for µ and we
  • want the margin of error to be 0.2.

36
We want margin of error (ME) to be 0.2.
Calculate the sample size?
This means we need at least a sample of size 829
to achieve this margin of error.
37
Exercise 7.4
  • To determine the diameter of Venus, an astronomer
    makes 36 measurements of the diameter and finds
  • miles. Assuming
    miles, find a 95 confidence interval
    estimate of the diameter of Venus. What sample
    size is required so that the margin of error in
    determining the diameter of Venus is only 50
    miles.

38
  • Answer 7.4
  • (7746.73, 7949.27)
  • 148
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