• Study Resource
• Explore

Survey

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

German tank problem wikipedia, lookup

Student's t-test wikipedia, lookup

Taylor's law wikipedia, lookup

Bootstrapping (statistics) wikipedia, lookup

Misuse of statistics wikipedia, lookup

Degrees of freedom (statistics) wikipedia, lookup

Transcript
```6.2 Confidence Intervals for
the Mean (Small Samples)
Statistics
Mrs. Spitz
Spring 2009
Objectives/Assignment
How to interpret the t-distribution and
use a t-distribution table
 How to construct confidence intervals
when n < 30 and  is unknown


Assignment: pp. 271-273 #1-26
The t-Distribution

In many real-life situations, the population
standard deviation is unknown. Moreover,
because of various constraints such as time
and cost, it is often not practical to collect
samples of size 30 or more. So, how can you
construct a confidence interval for a population
mean given such circumstances? If the
random variable is normally distributed (or
approximately normal), the sampling
distribution for x is a t-distribution.
Definition continued . . .
Note:

Table 5 of Appendix B lists critical values
of t for selected confidence intervals and
degrees of freedom. Pg. A20
Concept: Degrees of freedom

Suppose there are an equal number of
chairs in a classroom as there are
students: 25 chairs and 25 students.
Each of the first 24 students to enter the
classroom has a choice as to which chair
he or she will sit in. There is no freedom
of choice, however, for the 25th student
who enters the room.
Example 1: Finding Critical Values
of t

Find the critical value tc, for a 95% confidence
when the sample size is 15.
 SOLUTION: Because n = 15, the degrees of
freedom are:
d.f. = n – 1 = 15 – 1 = 14
A portion of Table 5 is shown. Using d.f. = 14
and c = 0.95, you can find the critical value, tc,
as shown by the highlighted areas in the table.
The graph shows the t-distribution for 14
degrees of freedom, c = 0.95 and tc = 2.145
Note:
 After
30 d.f., the t-values are close
to the z-values. Moreover, the
values in the table that show ∞ d.f.
correspond EXACTLY to the normal
distribution values.
Try it yourself #1:

Find the critical value tc, for a 90% confidence
when the sample size is 22.
 SOLUTION: Because n = 22, the degrees of
freedom are:
d.f. = n – 1 = 22 – 1 = 21
A portion of Table 5 is shown. Using d.f. = 21
and c = 0.90, you can find the critical value, tc,
as shown by the highlighted areas in the table.
Three things to do:
A. Identify the degrees of freedom: 21
B. Identify the level of confidence: 0.90
C. Use Table 5 to find t: 1.721
Study Tip:

Unlike the z-table, critical values for a
specific confidence interval can be found
in the column headed by c in the
appropriate d.f. row. (The symbol
be explained in chapter 7.)
∝ will
Confidence Intervals and tDistributions

Constructing a confidence interval using
the t-distribution is similar to constructing
a confidence interval using the normal
distribution—both use a point estimate x
and a maximum error of estimate, E.
Another Study Tip

Before using the t-distribution to
construct a confidence interval, you
should check that n < 30,  is unknown,
and the population is approximately
normal.
Ex. 2: Constructing a Confidence
Interval

You randomly select 16 restaurants and
measure the temperature of the coffee
sold at each. The sample mean
temperature is 162〫F with a standard
deviation of 10 〫F. Find the 95%
confidence interval for the mean
temperature. Assume the temperatures
are approximately normally distributed.
SOLUTION:
Because the sample size is less than 30,
 is unknown, and the temperatures are
approximately normally distributed, you
can use the t-distribution. Using n = 16,
x is 162, s = 10, c = 0.95 and d.f. =15, you
can use Table 5 to find that tc =

Step 3: Maximum error of Estimate, E.
Step 4: Left/Right endpoints by adding and
subtracting from the mean.
Ex. 3: Constructing a Confidence Interval

You randomly select 20 mortgage
institutions and determine the current
mortgage interest rate at each. The
sample mean rate is 6.93% with a
sample standard deviation of 0.42%.
Find the 99% confidence interval for the
mean mortgage rate. Assume the
interest rates are approximately normally
distributed.
Sample size is less than 30,  is
unknown and the interest rates are
approximately normally distributed so we
can use the t-distribution.
 n=20, x = 6.93, s = 0.42, c = 0.99, and
d.f. = 19.
 Find the maximum error of estimate at
the 99% confidence interval:

Step 3: Maximum Error of Estimate
x
Flowchart will help!
Ex. 4: Choosing the Normal or t-Distribution

You randomly select 25 newly constructed
houses. The sample mean construction cost
is \$181,000 and the population standard
deviation is \$28,000. Assuming construction
costs are normally distributed, should you use
the normal distribution, the t-distribution or
neither to construct a 95% confidence interval
for the mean construction cost? Explain your
reasoning.
Ex. 4: Choosing the Normal or t-Distribution

SOLUTION: Because the population is
normally distributed and the standard
deviation is known, you should use the
normal distribution.
Try it yourself #4

You randomly select 18 adult male athletes
and measure the resting heart rate of each.
The sample mean heart rate is 64 beats per
minute. Assuming that the heart rates are
normally distributed, should you use the
normal distribution, the t-distribution or neither
to construct a 90% confidence interval for the
mean heart rate? Explain your reasoning.
Flowchart will help!
Is n ≥ 30?
NO, IT IS 18.
Is population normally
or approximately
normally distributed?
Yes, normally
distributed.
Is  known?
No, sample
standard deviation
only.
```
Related documents