1 Pertemuan 07 Pendugaan Selang Parameter Matakuliah:A0392-Statistik Ekonomi Tahun: 2006.
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Transcript of 1 Pertemuan 07 Pendugaan Selang Parameter Matakuliah:A0392-Statistik Ekonomi Tahun: 2006.
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Pertemuan 07
Pendugaan Selang Parameter
Matakuliah :A0392-Statistik Ekonomi
Tahun : 2006
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Outline Materi :
• Pendugaan selang rata-rata
• Pendugaan selang beda rata-rata
• Pendugaan proporsi dan beda proporsi
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Basic Business Statistics (9th Edition)
Confidence Interval Estimation
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Proses pendugaan parameter
• Estimation Process
• Point Estimates
• Interval Estimates
• Confidence Interval Estimation for the Mean ( Known)
• Determining Sample Size
• Confidence Interval Estimation for the Mean ( Unknown)
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Pendugaan selang parameter
• Confidence Interval Estimation for the Proportion
• Confidence Interval Estimation for Population Total
• Confidence Interval Estimation for Total Difference in the Population
• Estimation and Sample Size Determination for Finite Population
• Confidence Interval Estimation and Ethical Issues
(continued)
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Estimation Process
Mean, , is unknown
Population Random Sample I am 95%
confident that is between 40 &
60.
Mean X = 50
Sample
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Point Estimates
Estimate Population
Parameters …
with SampleStatistics
Mean
Proportion
Variance
Difference
p
2
1 2
X
SP
2S
1 2X X
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Interval Estimates
• Provide Range of Values– Take into consideration variation in sample
statistics from sample to sample– Based on observation from 1 sample– Give information about closeness to unknown
population parameters– Stated in terms of level of confidence
• Never 100% sure
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Confidence Interval Estimates
Mean
Unknown
ConfidenceIntervals
Proportion
Known
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Confidence Interval for( Known)
• Assumptions– Population standard deviation is known– Population is normally distributed– If population is not normal, use large sample
• Confidence Interval Estimate–
– is called the sampling error or margin of error
/ 2 / 2X Z X Zn n
Standard Error
Critical Value
/ 2e Zn
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Elements of Confidence Interval Estimation
• Level of Confidence– Confidence that the interval will contain the
unknown population parameter
• Precision (Range)– Closeness to the unknown parameter
• Cost– Cost required to obtain a sample of size n
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Level of Confidence
• Denoted by
• A Relative Frequency Interpretation– In the long run, of all the
confidence intervals that can be constructed will contain (bracket) the unknown parameter
• A Specific Interval Will Either Contain or Not Contain the Parameter– No probability involved in a specific interval
100 1 %
100 1 %
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Interval and Level of Confidence
Confidence Intervals
Intervals extend from
to
of intervals constructed contain ;
do not.
_Sampling Distribution of the Mean
XX Z
X/ 2
/ 2
XX
1
XX Z
1 100%
100 %
/ 2 XZ / 2 XZ
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Example
A random sample of 15 stocks traded on the NASDAQ showed an average shares traded to be 215000. From past experience, it is believed that the population standard deviation of shares traded is 195000 and the shares traded are very close to a normal distribution. Construct a 99% confidence interval for the average shares traded on the NASDAQ. Interpret your result.
Confidence Interval Estimate for the Mean
Population Standard Deviation 195000Sample Mean 215000Sample Size 15Confidence Level 99%Standard Error of the Mean 50348.7835Z Value -2.57583451Interval Half Width 129690.1343Interval Lower Limit 85309.86569Interval Upper Limit 344690.1343
PHStat output
85309 344690 The 99% CI for the population mean:
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Example: Interpretation
(continued)
We are 99% confident that the population average number of shares traded on the NASDAQ is between 85309 and 344690.
If all possible samples of size 15 are taken and the corresponding 99% confidence intervals are constructed, 99% of the confidence intervals that are constructed will contain the true unknown population mean.
For this particular confidence interval [85309, 344690], the unknown population mean can either be in the interval or not in the interval. It is, therefore, incorrect to state that the probability is 99% that the unknown population mean will be in the interval [85309, 344690].
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Example: Interpretation
(continued)
Using the confidence interval method on repeated sampling, the probability that we will have constructed a confidence interval that will contain the unknown population mean is 99%.
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Obtaining Confidence Intervalin PHStat
• PHStat | Confidence Interval | Estimates for the Mean, Sigma Known
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Factors Affecting Interval Width(Precision)
• Data Variation– Measured by
• Sample Size–
• Level of Confidence–
Intervals Extend from
© 1984-1994 T/Maker Co.
X - Z to X + Z xx
Xn
100 1 %
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Determining Sample Size (Cost)
Too Big:
• Requires more resources
Too small:
• Won’t do the job
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Determining Sample Sizefor Mean
What sample size is needed to be 90% confident of being correct within ± 5? A pilot study suggested that the standard deviation is 45.
Round Up
2 22 2
2 2
1.645 45219.2 220
Error 5
Zn
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Determining Sample Size for Mean in PHStat
• PHStat | Sample Size | Determination for the Mean …
• Example in Excel Spreadsheet
Microsoft Excel Worksheet
Sample Size Determination
DataPopulation Standard Deviation 45Sampling Error 5Confidence Level 90%
Z Value -1.644853Calculated Sample Size 219.1488528
Sample Size Needed 220Result
Intemediate Calculations
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• Assumptions– Population standard deviation is unknown– Population is normally distributed– If population is not normal, use large sample
• Use Student’s t Distribution
• Confidence Interval Estimate–
Confidence Interval for( Unknown)
/ 2, 1 / 2, 1n n
S SX t X t
n n
Margin of ErrorStandard Error
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Student’s t Distribution
Zt
0
t (df = 5)
t (df = 13)Bell-ShapedSymmetric
‘Fatter’ Tails
Standard Normal
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Student’s t Table
Upper Tail Area
df .25 .10 .05
1 1.000 3.078 6.314
2 0.817 1.886 2.920
3 0.765 1.638 2.353
t0 2.920t Values
Let: n = 3 df = n - 1 = 2 = .10 /2 =.05
/ 2 = .05
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Example
/ 2, 1 / 2, 1
8 850 2.0639 50 2.0639
25 2546.69 53.30
n n
S SX t X t
n n
A random sample of 25 has 50 and 8.
Set up a 95% confidence interval estimate for
n X S
We are 95% confident that the unknown true population
mean is somewhere between 46.69 and 53.30.
.
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• PHStat | Confidence Interval | Estimate for the Mean, Sigma Unknown
• Example in Excel Spreadsheet
Confidence Interval for( Unknown) in PHStat
Microsoft Excel Worksheet
Confidence Interval Estimate for the Mean
DataSample Standard Deviation 8Sample Mean 50Sample Size 25Confidence Level 95%
Standard Error of the Mean 1.6Degrees of Freedom 24t Value 2.063898137Interval Half Width 3.302237019
Interval Lower Limit 46.70Interval Upper Limit 53.30
Intermediate Calculations
Confidence Interval
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Confidence Interval Estimatefor Proportion
• Assumptions– Two categorical outcomes– Population follows binomial distribution– Normal approximation can be used if
and – Confidence Interval Estimate–
5np 1 5n p
/ 2 / 2
1 1S S S SS S
p p p pp Z p p Z
n n
Margin of Error
Standard Error
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Example
A random sample of 400 voters showed that 32 preferred Candidate A. Set up a 95% confidence interval estimate for p.
/ /
1 1
.08 1 .08 .08 1 .08.08 1.96 .08 1.96
400 400.053 .107
s s s ss s
p p p pp Z p p Z
n n
p
p
We are 95% confident that the proportion of voters who prefer Candidate A is somewhere between 0.053 and 0.107.
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Confidence Interval Estimate for Proportion in PHStat
• PHStat | Confidence Interval | Estimate for the Proportion …
• Example in Excel Spreadsheet
Microsoft Excel Worksheet
Confidence Interval Estimate for the Mean
DataSample Size 400Number of Successes 32Confidence Level 95%
Sample Proportion 0.08Z Value -1.95996108Standard Error of the Proportion 0.01356466Interval Half Width 0.026586206
Interval Lower Limit 0.053413794Interval Upper Limit 0.106586206
Intermediate Calculations
Confidence Interval
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Determining Sample Sizefor Proportion
Out of a population of 1,000, we randomly selected 100, of which 30 were defective. What sample size is needed to be within ± 5% with 90% confidence?
Round Up
2 2
2 2
1 1.645 0.3 0.7
Error 0.05227.3 228
Z p pn
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Determining Sample Size for Proportion in PHStat
• PHStat | Sample Size | Determination for the Proportion …
• Example in Excel Spreadsheet
Microsoft Excel Worksheet
Sample Size Determination
DataEstimate of True Proportion 0.3Sampling Error 0.05Confidence Level 90%
Z Value -1.644853Calculated Sample Size 227.265477
Sample Size Needed 228
Intermediate Calculations
Result
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Confidence Interval for Population Total Amount
• Point Estimate–
• Confidence Interval Estimate
–
NX
/ 2, 1 1n
N nSNX N t
Nn
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Confidence Interval for Population Total: Example
An auditor is faced with a population of 1000 vouchers and wishes to estimate the total value of the population of vouchers. A sample of 50 vouchers is selected with the average voucher amount of $1076.39, standard deviation of $273.62. Set up the 95% confidence interval estimate of the total amount for the population of vouchers.
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Example Solution
/ 2, 1
1000 50 $1076.39 $273.62
1
273.62 1000 501000 1076.39 1000 2.0096
1000 11001,076,390 75,830.85
n
N n X S
N nSNX N t
Nn
The 95% confidence interval for the population total amount of the vouchers is between 1,000,559.15 and 1,152,220.85.
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Example Solution in PHStat
• PHStat | Confidence Intervals | Estimate for the Population Total
• Excel Spreadsheet for the Voucher Example
Microsoft Excel Worksheet
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Confidence Interval for Total Difference in the Population
• Point Estimate
– where is the sample average
difference
• Confidence Interval Estimate
–
– where
ND 1
n
ii
DD
n
/ 2, 1 1
Dn
N nSND N t
Nn
2
1
1
n
ii
D
D DS
n
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Estimation for Finite Population
• Samples are Selected Without Replacement– Confidence interval for the mean
( unknown)
•
– Confidence interval for proportion
•
/ 2, 1 1n
N nSX t
Nn
/ 2
1
1S S
S
p p N np Z
n N
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Sample Size (n ) Determination for Finite Population
• Samples are Selected Without Replacement–
– When estimating the mean
•
– When estimating the proportion
•
2 2/ 2
0 2
Zn
e
2/ 2
0 2
1Z p pn
e
0
0 1
n Nn
n N
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Ethical Issues
• Confidence Interval (Reflects Sampling Error) Should Always Be Reported Along with the Point Estimate
• The Level of Confidence Should Always Be Reported
• The Sample Size Should Be Reported
• An Interpretation of the Confidence Interval Estimate Should Also Be Provided
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Chapter Summary
• Illustrated Estimation Process
• Discussed Point Estimates
• Addressed Interval Estimates
• Discussed Confidence Interval Estimation for the Mean ( Known)
• Addressed Determining Sample Size
• Discussed Confidence Interval Estimation for the Mean ( Unknown)
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Chapter Summary
• Discussed Confidence Interval Estimation for the Proportion
• Addressed Confidence Interval Estimation for Population Total
• Discussed Confidence Interval Estimation for Total Difference in the Population
• Addressed Estimation and Sample Size Determination for Finite Population
• Addressed Confidence Interval Estimation and Ethical Issues
(continued)