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Estimation

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0% found this document useful (0 votes)
181 views11 pages

Estimation

Uploaded by

Gizaw Fulas
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PPT, PDF, TXT or read online on Scribd
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6-1

Chapter 8

Estimation and
Hypothesis Testing
6-2

Introduction

 Statistical inference - inferences about a population


are made on the basis of a sample result
 Statistical inference divided in to two: estimation

and hypothesis testing


 Estimation is concerned with estimating the values of
specific population
 hypothesis testing is concerned with testing whether the

value of a population parameter is equal to some specific


value
6-3

8.1 Point and Interval Estimation of the


Mean
• Estimator of a population parameter is a sample
statistic used to estimate or predict the population
parameter.
• Estimate of a parameter is a particular numerical
value of a sample statistic obtained through
sampling.
• Point estimate is a single value used as an estimate
of a population parameter
6-4

• Consider the following statements:


x = 550
• A single-valued estimate that conveys little information
about the actual value of the population mean.
We are 99% confident that  is in the interval [449,551]
• An interval estimate which locates the population mean
within a narrow interval, with a high level of confidence.
We are 90% confident that  is in the interval [400,700]
• An interval estimate which locates the population mean
within a broader interval, with a lower level of confidence.
6-5

Types of Estimators

• Point Estimate
A single-valued estimate.
A single element chosen from a sampling distribution.
Conveys little information about the actual value of the
population parameter, about the accuracy of the estimate .
• Confidence Interval or Interval Estimate
An interval or range of values believed to include the
unknown population parameter.
Associated with the interval is a measure of the confidence
we have that the interval does indeed contain the parameter of
interest.
6-6

Confidence Interval or Interval


Estimate
• Confidence interval/interval estimate: is a range or
interval of numbers believed to include an unknown
population parameter.
• Associated with the interval is a measure of the
confidence we have that the interval does indeed
contain the parameter of interest.
• A confidence interval/interval estimate has two
components:
A range or interval of values
An associated level of confidence
6-7

Case 1: Confidence Interval for 


When the Population Is Normal

When is Known,
- The (1 – α)100% confidence interval for the population mean
µ is:
  
 X Z 2 
 n

• When is Unknown, and small sample size (n<30)


- The (1 – α)100% confidence interval for µ becomes:

 s 
 X t 2 ( n  1) 
 n
6-8

Case 2: Confidence Interval for 


When the Population Is non Normal
The sample should be large (n>=30) (the central limit
theorem is used to approximate the distribution

When is Known,
- The (1 – α)100% confidence interval for the population mean
µ is:
  
 X Z 2 
 n
• When is Unknown,
- The (1 – α)100% confidence interval for µ becomes:
 s 
 X Z 2 
 n
6-9

Critical Values of z and Levels of


Confidence

(1   )
 z
Stand ard N o rm al Distrib utio n

2 2
0.4
(1   )

0.99 0.005 2.576


0.3

f(z)
0.2

0.98 0.010 2.326 0.1  


2 2
0.95 0.025 1.960 0.0
-5 -4 -3 -2 -1 0 1 2 3 4 5

0.90 0.050 1.645  z


2
Z z
2

0.80 0.100 1.282


6-10


Example 1: From a normal population, a sample of size
25 was randomly drawn and a mean of 32 was found.
Given that the population standard deviation is 4.2. Find
a) A 95% confidence interval for the population mean. (30.35, 33.65)
b) A 99% confidence interval for the population mean. (29.83, 34.17)
• Example 2: A company that delivers packages within a large
metropolitan area claims that it takes an average of 28 minutes
for a package to be delivered from your door to the destination.
A random sample of 100 packages took a mean time of 31.5
minutes with standard deviation of 5 minutes. Construct a 95%
confidence interval for the average delivery times of all
packages. (30.52, 32.48)
6-11


Example 3: A stock market analyst wants to estimate the average
return on a certain stock. A random sample of 15 days yields an
average (annualized) return of 10.37% and a standard deviation of
3.5%. Assuming a normal population of returns, give a 95%
confidence interval for the average return on this stock.
(8.43,. 12.31))

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