Estimates and Sample Size with One Sample - PowerPoint PPT Presentation

1 / 29
About This Presentation
Title:

Estimates and Sample Size with One Sample

Description:

The standard deviation of the pulse rate is known to be 5 beats per minute. A sample of 30 users had an average pulse rate of 104 beats per minute. ... – PowerPoint PPT presentation

Number of Views:109
Avg rating:3.0/5.0
Slides: 30
Provided by: GordonRo2
Category:
Tags: estimates | one | sample | size

less

Transcript and Presenter's Notes

Title: Estimates and Sample Size with One Sample


1
Chapter 6
6-1
  • Estimates and Sample Size with One Sample

2
Outline
6-2
  • 6-1 Introduction
  • 6-3 Estimating a Population Mean with ?
    known?
  • 6-4 Estimating a Population Mean with ?
    unknown?

3
Objectives
6-4
  • Find the confidence interval for the mean
    when ? is known or n?? 30.
  • Determine the minimum sample size for finding a
    confidence interval for the mean.
  • Find the confidence interval for the mean when ?
    is unknown and n?? 30.

4
6-3 Confidence Intervals for the Mean (? known
or n ? 30) and Sample Size
6-6






A point estimate is a specific numerical value
estimate of a parameter. The best estimate of
the population mean is thesample mean .





?



X







5
6-3 Three Properties of a Good
Estimator
6-7
  • The estimator must be an unbiased estimator.
    That is, the expected value or the mean of the
    estimates obtained from samples of a given size
    is equal to the parameter being estimated.

6
6-3 Three Properties of a Good
Estimator
6-8
  • The estimator must be consistent. For a
    consistent estimator, as sample size increases,
    the value of the estimator approaches the value
    of the parameter estimated.

7
6-3 Three Properties of a Good
Estimator
6-9
  • The estimator must be a relatively efficient
    estimator. That is, of all the statistics that
    can be used to estimate a parameter, the
    relatively efficient estimator has the smallest
    variance.

8
6-3 Confidence Intervals
6-10
  • An interval estimate of a parameter is an
    interval or a range of values used to estimate
    the parameter. This estimate may or may not
    contain the value of the parameter being
    estimated.

9
6-3 Confidence Intervals
6-11
  • A confidence interval is a specific interval
    estimate of a parameter determined by using data
    obtained from a sample and the specific
    confidence level of the estimate.

10
6-3 Confidence Intervals
6-12
  • The confidence level of an interval estimate of a
    parameter is the probability that the interval
    estimate will contain the parameter.

11
6-3 Formula for the Confidence Interval of the
Mean for a Specific ?
6-13
  • The confidence level is the percentage equivalent
    to the decimal value of 1 ?.

12
6-3 Maximum Error of Estimate or Margin of Error
(E)
6-14
  • The maximum error of estimate or
  • margin of error (E) is the maximum difference
    between the point estimate of a parameter and the
    actual value of the parameter.

13
6-3 Confidence Intervals - Example
6-15
  • The president of a large university wishes to
    estimate the average age of the students
    presently enrolled. From past studies, the
    standard deviation is known to be 2 years. A
    sample of 50 students is selected, and the mean
    is found to be 23.2 years. Find the 95
    confidence interval of the population mean.

14
6-3 Confidence Intervals - Example
6-16
15
6-3 Confidence Intervals - Example
6-17
2
2
?
?
?
?
?
23
2
23.2
.
(1.96)
(
)
(1.96)
(
)
?50
?50
?
?
?
?
?
23
2
0
6
23
2
0
6
.
.
.
.
?
?
?
22
6
23
8
.
.
or 23.2 0.6 years.
95
,
,
Hence
the
president
can
say
with




,
confidence
that
the
average
age



22
6
23
8
.
.
of
the
students
is
between
and







50
,
.
years
based
on
students



16
6-3 Confidence Intervals - Example
6-18
  • A certain medication is known to increase the
    pulse rate of its users. The standard deviation
    of the pulse rate is known to be 5 beats per
    minute. A sample of 30 users had an average
    pulse rate of 104 beats per minute. Find the 99
    confidence interval of the true mean.

17
6-3 Confidence Intervals - Example
6-19
18
6-3 Confidence Intervals - Example
6-20
5
5
?
?
?
?
?
104
(2.58)
104
.
(
)
(
)
(2.58)
30
30
?
?
?
?
?
104
2
4
104
2
4
.
.
?
?
?
101
6
106
4
.
.
.
99
,
,
Hence
one
can
say
with







,
confidence
that
the
average
pulse



101
6
106.4
.
rate
is
between
and





beats per minute, based on 30 users.
19
6-3 Formula for the Minimum Sample Size Needed
for an Interval Estimate of the Population Mean
6-21
20
6-3 Minimum Sample Size Needed for an Interval
Estimate of the Population Mean - Example
6-22
  • The college president asks the statistics
    teacher to estimate the average age of the
    students at their college. How large a sample is
    necessary? The statistics teacher decides the
    estimate should be accurate within 1 year and be
    99 confident. From a previous study, the
    standard deviation of the ages is known to be 3
    years.

21
6-3 Minimum Sample Size Needed for an Interval
Estimate of the Population Mean - Example
6-23
22
6-4 Characteristics of the t-Distribution
6-24
  • The t-distribution shares some characteristics of
    the normal distribution and differs from it in
    others. The t-distribution is similar to the
    standard normal distribution in the following
    ways
  • It is bell-shaped.
  • It is symmetrical about the mean.

23
6-4 Characteristics of thet-Distribution
6-25
  • The mean, median, and mode are equal to 0 and are
    located at the center of the distribution.
  • The curve never touches the x axis.
  • The t distribution differs from the standard
    normal distribution in the following ways

24
6-4 Characteristics of thet-Distribution
6-26
  • The variance is greater than 1.
  • The t distribution is actually a family of curves
    based on the concept of degrees of freedom, which
    is related to the sample size.
  • As the sample size increases, the t distribution
    approaches the standard normal distribution.

25
6-4 Standard Normal Curve and the
t Distribution
6-27
26
6-4 Formula for the Confidence Interval of the
Mean for a Specific ?
6-13
  • When n lt 30 and s is unknown use t-distribution
    with degrees of freedom n 1.

27
6-4 Confidence Interval for the Mean (?
unknown and n lt 30) - Example
6-28
  • Ten randomly selected automobiles were stopped,
    and the tread depth of the right front tires were
    measured. The mean was 0.32 inches, and the
    standard deviation was 0.08 inches. Find the 95
    confidence interval of the mean depth. Assume
    that the variable is approximately normally
    distributed.

28
6-4 Confidence Interval for the Mean (?
unknown and n lt 30) - Example
6-29
  • Since ? is unknown and s must replace it, the t
    distribution must be used with ? 0.05. Hence,
    with 9 degrees of freedom, t?/2 2.262 (see
    Table F in text).
  • From the next slide, we can be 95 confident that
    the population mean is between 0.26 and 0.38.

29
6-4 Confidence Interval for the Mean (?
unknown and n lt 30) - Example
6-30
Thus
the
confidence




95
interval
of
the
population
mean
is
found
by






substituting in

s
s
?
?
?
?
?
?
?
?
?
?
?
?
?
X
t
X
t

?
?
?
?
?n
?n
?
?
2
2
0.08
0.08
?
?
?
?
?
?
?
?
?
?
?
?
0.32

(2.262)
(2.262)
0
32
.
?
?
?
?
?10
?10
?
?
?
0
26
0
38
.
.
Write a Comment
User Comments (0)
About PowerShow.com