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AP Statistics Chap 10-1
Confidence Intervals

AP Statistics Chap 10-2
Confidence Intervals
Population Mean
σ Unknown(Lock 6.5)
ConfidenceIntervals
PopulationProportion(Lock 6.1)
σ Known(Lock 5.2)

Central Limit Theorem
AP Statistics Chap 10-3
Normal if:Asymmetric: 30+Symmetric: 15+Normal: >1

AP Statistics Chap 10-4
Confidence Interval for μ(σ Known)
Assumptions Population standard deviation σ is known Population is normally distributed If population is not normal, use large sample
Confidence interval estimate
n
σzx α/2

AP Statistics Chap 10-5
Common Levels of Confidence
Commonly used confidence levels are 90%, 95%, and 99%
Confidence Level
Confidence Coefficient,
z value,
1.28
1.645
1.96
2.33
2.58
3.08
3.27
.80
.90
.95
.98
.99
.998
.999
80%
90%
95%
98%
99%
99.8%
99.9%
1 /2z

AP Statistics Chap 10-6
Finding the Critical Value
Consider a 95% confidence interval:
z.025= -1.96 z.025= 1.96
.951
.0252
α .025
2
α
Point EstimateLower Confidence Limit
UpperConfidence Limit
z units:
x units: Point Estimate
0
1.96zα/2

Confidence Intervals
90% Samples
95% Samples
99% Samples
+1.65x +2.58x
x_
X
+1.96x
-2.58x -1.65x
-1.96x
X= ± Zx

AP Statistics Chap 10-8
μμx
Interval and Level of Confidence
Confidence Intervals
Intervals extend from
to
100(1-)%of intervals constructed contain μ;
100% do not.
Sampling Distribution of the Mean
n
σzx /2
n
σzx /2
x
x1
x2
/2 /21

AP Statistics Chap 10-9
Margin of Error(MoE)
Margin of Error (e): the amount added and subtracted to the point estimate to form the confidence interval
n
σzx /2
n
σze /2
Example: Margin of error for estimating μ, σ known:

AP Statistics Chap 10-10
Factors Affecting MoE
Data variation, σ : e as σ
Sample size, n : e as n
Level of confidence, 1 - : e if 1 -
n
σze /2

AP Statistics Chap 10-11
Example 1
A sample of 11 circuits from a large normal population has a mean resistance of 2.20 ohms. We know from past testing that the population standard deviation is .35 ohms.
Determine a 95% confidence interval for the true mean resistance of the population.

AP Statistics Chap 10-12
Example 1
A sample of 11 circuits from a large normal population has a mean resistance of 2.20 ohms. We know from past testing that the population standard deviation is .35 ohms.
(continued)
n
σ /2zx Solution:
2.20±1.96(.35/sqrt(11)
2.20±.2068
[1.99, 2.4068]

Z-Interval w/ Calculator
AP Statistics Chap 10-13

AP Statistics Chap 10-14
Interpretation
We are 95% confident that the true mean resistance is between 1.9932 and 2.4068 ohms
Although the true mean may or may not be in this interval, 95% of intervals formed in this manner will contain the true mean
An incorrect interpretation is that there is 95% probability that this
interval contains the true population mean.
(This interval either does or does not contain the true mean, there is no probability for a single interval)

Thinking Challenge
You’re a Q/C inspector for Gallo. The for 2-liter bottles is .05 liters. A random sample of 100 bottles showsX = 1.99 liters. What is the 90% confidence interval estimate of the true mean amount in 2-liter bottles?
2 liter
© 1984-1994 T/Maker Co.
2 liter

Confidence Interval Solution

AP Statistics Chap 10-17
Computer Simulation

AP Statistics Chap 10-18
Example 2
Tim Kelley weighs himself once a week for several years. Last month he weighed himself 4 times with an average of 190.5. Examination of Tim’s past data reveals that over relatively short periods of time, his weight measurements are approximately normal with a standard deviation of about 3. Find a 90% confidence interval for his mean weight for last month. Then, find a 99% confidence interval.
97.192,03.1884
3645.15.190
CI
37.194,63.1864
358.25.190
CI

AP Statistics Chap 10-19
Example 2
Suppose Tim had only weighed himself once last month and that his one observation was x=190.5 (the same as the mean before). Estimate µ with 90% confidence.
(continued)
24.198,76.1821
3645.15.190
CI

AP Statistics Chap 10-20
Example 2
Tim wants to have a margin of error of only 2 pounds with 95% confidence. How many times must he weigh himself to achieve this goal?
(continued)
93
96.12 nn

AP Statistics Chap 10-21
Confidence Intervals
with
Unknown Population
Standard Deviation

AP Statistics Chap 10-22
Confidence Intervals
Population Mean
σ Unknown
ConfidenceIntervals
PopulationProportion
σ Known

AP Statistics Chap 10-23
If the population standard deviation σ is unknown, we can substitute the sample standard deviation, s
This introduces extra uncertainty, since s is variable from sample to sample
So we use the t distribution instead of the normal distribution
Confidence Interval for μ(σ Unknown)

AP Statistics Chap 10-24
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 μ(σ Unknown)
n
stx /2
(continued)

AP Statistics Chap 10-27
Student’s t Distribution
t0
t (df = 5)
t (df = 13)t-distributions are bell-shaped and symmetric, but have ‘fatter’ tails than the normal
Standard Normal
(t with df = )
Note: t z as n increases

AP Statistics Chap 10-28
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 2.920The body of the table contains t values, not probabilities
Let: n = 3 df = n - 1 = 2 = .10 /2 =.05
/2 = .05

AP Statistics Chap 10-29
t distribution values
With comparison to the z value
Confidence t t t z Level (10 d.f.) (20 d.f.) (30 d.f.) ____
.80 1.372 1.325 1.310 1.28
.90 1.812 1.725 1.697 1.64
.95 2.228 2.086 2.042 1.96
.99 3.169 2.845 2.750 2.58
Note: t z as n increases

AP Statistics Chap 10-30
Example
A random sample of n = 25 has x = 50 and s = 8. Form a 95% confidence interval for μ
2.0639t so, 24, 1– n d.f. .025,241n,/2 t
25
8(2.0639)50
n
stx /2
CI = 46.698, 53.302
The confidence interval is:

Thinking Challenge
You’re a time study analyst in manufacturing. You’ve recorded the following task times (min.): 3.6, 4.2, 4.0, 3.5, 3.8, 3.1.What is the 90% confidence interval estimate of the population mean task time?

Confidence Interval Solution*
X = 3.7 S = 3.8987 n = 6, df = n - 1 = 6 - 1 = 5 S / n = 3.99 / 6 = 1.592
t.05,5 = 2.0150
3.7 - (2.015)(1.592) 3.7 + (2.015)(1.592)
0.492 6.908

AP Statistics Chap 10-33
Approximation for Large Samples
Since t approaches z as the sample size increases, an approximation is sometimes used when n 30:
n
stx /2
n
szx /2
Correct formula
Approximation for large n

AP Statistics Chap 10-36
If σ is unknown
If unknown, σ can be estimated when using the required sample size formula
Use a value for σ that is expected to be at least as large as the true σ
Select a pilot sample and estimate σ with the sample standard deviation, s

AP Statistics Chap 10-37
Chapter 10
Confidence Intervals
for
Population Proportions

AP Statistics Chap 10-38
Confidence Intervals
Population Mean
σ Unknown
ConfidenceIntervals
PopulationProportion
σ Known

AP Statistics Chap 10-39
Confidence Intervals for the Population Proportion, p
An interval estimate for the population proportion ( p ) can be calculated by adding an allowance for uncertainty to the sample proportion ( ) p̂

AP Statistics Chap 10-40
Confidence Intervals for the
Population Proportion, p
Recall that the distribution of the sample proportion is approximately normal if the sample size is large, with standard deviation
We will estimate this with sample data:
(continued)
n
)p(1ps
p
n
p)p(1σp

AP Statistics Chap 10-41
Confidence interval endpoints
Upper and lower confidence limits for the population proportion are calculated with the formula
where z is the standard normal value for the level of confidence desired p is the sample proportion n is the sample size
n
)p(pzp /2
1

AP Statistics Chap 10-42
Example
A random sample of 100 people
shows that 25 are left-handed.
Form a 95% confidence interval for
the true proportion of left-handers

AP Statistics Chap 10-43
Example A random sample of 100 people shows
that 25 are left-handed. Form a 95% confidence interval for the true proportion of left-handers.
1.
2.
3.
.0433 .25(.75)/n)/np(1pS
.2525/100 p
p
0.3349 . . . . . 0.1651
(.0433) 1.96 .25
(continued)

AP Statistics Chap 10-44
Interpretation
We are 95% confident that the true percentage of left-handers in the population is between
16.51% and 33.49%.
Although this range may or may not contain the true proportion, 95% of intervals formed from samples of size 100 in this manner will contain the true proportion.

AP Statistics Chap 10-45
Changing the sample size
Increases in the sample size reduce the width of the confidence interval.
Example: If the sample size in the above example is
doubled to 200, and if 50 are left-handed in the sample, then the interval is still centered at .25, but the width shrinks to
.19 …… .31

Estimation Example Proportion
A random sample of 400 graduates showed 32 went to grad school. Set up a 95% confidence interval estimate for p.

Estimation Example Proportion
A random sample of 400 graduates showed 32 went to grad school. Set up a 95% confidence interval estimate for p.
ˆ ˆ ˆ ˆˆ ˆ
α/2 α/2
p×( 1-p) p×( 1-p)p-Z × ≤p≤p+Z ×
n n
.08×( 1-.08) .08×( 1-.08).08-1.96× ≤p≤.08+1.96×
400 400
.053 p .107

Thinking Challenge
You’re a production manager for a newspaper. You want to find the % defective. Of 200 newspapers, 35 had defects. What is the 90% confidence interval estimate of the population proportion defective?

Confidence Interval Solution*
ˆ ˆ ˆ ˆˆ ˆ
a/2 a/2
p×( 1-p) p×( 1-p)p-z × ≤p≤p+z ×
n n
.175×( .825) .175×( .825).175-1.645× ≤p≤.175+1.645×
200 200.1308≤p≤.2192

AP Statistics Chap 10-50
Finding the Required Sample Size
for proportion problems
n
)p(pze /2
1
Solve for n:
Define the margin of error:
2/2
e
)p(pzn
12
p can be estimated with a pilot sample, if necessary (or conservatively use p = .50)

AP Statistics Chap 10-51
What sample size...?
How large a sample would be necessary to estimate the true proportion defective in a large population within 3%, with 95% confidence?
(Assume a pilot sample yields p = .12)

AP Statistics Chap 10-52
What sample size...?
Solution:For 95% confidence, use Z = 1.96E = .03p = .12, so use this to estimate p
So use n = 451
450.74(.03)
.12)(.12)(1(1.96)
e
)p(pzn
2
2/2
2
2 1
(continued)

AP Statistics Chap 10-54
Confidence Intervals
End
of
Basic Confidence Intervals