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TRANSCRIPT
Ø Point Estimate
Ø Calculating a Confidence Interval
Ø Interpreting a Confidence Interval
ØAccuracy of Confidence Intervals
Ø Sample Size Calculations
Confidence Intervals for a Population Mean
Lecture 18
Section 6.1
Four Stages of Statistics
• Data Collection þ
• Displaying and Summarizing Data þ
• Probability þ
• Inference• One Quantitative• Confidence Intervals
• Hypothesis Testing
• Inference for a Single Population Mean
• One Categorical
• One Quantitative and One Categorical
• Two Categorical
• Two Quantitative
Motivation: Confidence Intervals
• Scenario: SAT is designed to have normally distributed scores with mean 1000 and standard deviation 195.
• Question: How can we determine if 1000 is a plausible value for the average SAT score of Pitt students?
• Solution #1: Take a ______________________ of SAT scores from Pitt students, find the ________________, and see if it _________________• Problem #1: Cannot sample the ____________________ so we will not find ___
• Problem #2: ________________ exists from sample to sample so the sample mean !̅ will not be a ____________________________ of the population mean
• Problem #3: Cannot display the effect of taking _______________________
• Solution #2: Find an _________________________________ for what the mean SAT score of Pitt students _____________
Types of Estimates
• Point Estimate: a single value that is provided as the estimate of an unknown parameter in a population
• !̅ is a point estimate for "
• # is a point estimate for $
• &̂ is a point estimate for &
• Interval Estimate: an interval of plausible values for an unknown parameter; based on the sample, each value could reasonably be the value of the parameter
Example: Point Estimate
• Scenario: Take a random sample of 25 Pitt students and find a sample mean SAT score of 1250.
• Question: What notation and value should be used to represent a point estimate of the average SAT score of Pitt students?
• Answer: ______________________
• Question: What notation and value should be used to represent the true population mean SAT score of Pitt students?
• Answer: ____ à ___________________________
Example: Point Estimate
• Scenario: Take a random sample of 25 Pitt students and find a sample mean SAT score of 1250.
• Question: How certain are we that 1250 is the exact population mean SAT score for Pitt students?
• Answer: ________________________________• 1250 probably _________________________________________
• Solution: Use what we know about the _____________ in conjunction with the __________ to calculate an _____________________________
Confidence Interval
• Confidence Interval: interval of plausible values for an unknown parameter that is calculated from the responses in a sample• Provides us with a range of values that could be the true parameter
• Confidence Level: measure of how certain we are that the confidence interval contains the true population parameter• Denoted by 100 1 − ( % where ( is the total area being left out
•Most confidence intervals have the form:
Statistic ± Critical Value ∗ Standard Error
Depends on
confidence levelMargin of Error: maximum expected
difference between statistic and parameter
Point
Estimate
Example: Confidence Interval
• Scenario: Take a random sample of 25 Pitt students and find a sample mean SAT score of 1250.
• Goal: Calculate a 95% confidence interval for the true mean SAT score of Pitt students.
• Question: What values do we need to calculate the confidence interval?
• Answer:• Statistic: _____________
• Standard Error: _______________________
• Critical Value: ___________ bounding the _______________ of standard normal distribution
Example: Confidence Interval
• Question: How can we find the Z-scores bound the middle 95% of the standard normal distribution?
• Answer: _______________________________________________• Leaves out a total of ______
Note: Symmetry gives us the
upper critical value of ______.
Example: Confidence Interval
• Scenario: Take a random sample of 25 Pitt students and find a sample mean SAT score of 1250.
• Goal: Calculate a 95% confidence interval for the true mean SAT score of Pitt students.
• Answer: ________________________________• Lower Bound:
____________________________________ ___________________________________________
Upper Bound:
Example: Confidence Interval
• Scenario: Take a random sample of 25 Pitt students and find a sample mean SAT score of 1250. A 95% confidence interval for the average SAT score of Pitt students is (1173.56, 1326.44).
• Question: Is 1000 a plausible value for the average SAT score for Pitt students?
• Answer: ______• 95% confidence interval _______________________________
• 1000 appears to be ___________ because the entire interval is ____________
Confidence Interval for a Single Population Mean
• To estimate a single unknown population mean " using a confidence interval, use:
!̅ ± / ⁄9 :
$
;
where:• !̅: Sample mean
• / ⁄9 :: Critical value corresponding to confidence level 100 1 − ( %
• $: Population standard deviation
• ;: Sample size
Note: Should check to make sure the shape of the sample mean is normal before
calculating the confidence interval.
Critical Values
• Critical Value: multiplier in a confidence interval that tells how many standard error to extend in each direction from the statistic• A confidence interval for " when $ is known will always use <
• Critical values will come from a different distribution in other situations
• The table below shows critical values for typical confidence levels that use <:
Confidence Level Critical Value
80% 1.282
90% 1.645
95% 1.96
98% 2.326
99% 2.576
Example: 99% Confidence Interval
• Scenario: A random sample of the heights of 21 men found a sample mean of 70.6 inches. Assume the population standard deviation is 4 inches.
• Task: Calculate a 99% confidence interval for the mean height of males.
• Step #1: ______________________________• Histogram: _________________
• Skewness: _________________________________, but __________________
• Kurtosis: ___________________________________
Example: 99% Confidence Interval
• Scenario: A random sample of the heights of 21 men found a sample mean of 70.6 inches. Assume the population standard deviation is 4 inches.
• Task: Calculate a 99% confidence interval for the mean height of males.
• Step #2: ____________________________________
__________________________________________________________________________
Note: Even though the sample standard deviation was only 3.363, we still
use 4 because __________________________. It is always better to use the value
of parameters if they are __________.
Example: 99% Confidence Interval
• Scenario: A random sample of the heights of 21 men found a sample mean of 70.6 inches. Assume the population standard deviation is 4 inches.
• Question: How should the confidence interval be interpreted in the context of the situation?
• Answer: ________________________________________________________________ ___________________________________________________________________________• Interpretation of any confidence interval always includes:• __________________________
• ______________________________________________________
• _________________________________________
Example: Measuring Accuracy
• Scenario: IQ scores are known to be normally distributed with a population mean of 100 and a population standard deviation of 15. Take 10 random samples of size 25 and calculate a 90% confidence interval for each.
• Question: How many of these intervals would we expect to contain 100?
• Answer: _____• Confidence intervals are ___________________
• 90% confidence literally means 90% of the time the interval _____________ _______________________, but 10% of the time ____________________
• Confidence levels can always be interpreted as ___________________
Example: Measuring Accuracy
• Scenario: IQ scores are known to be normally distributed with a population mean of 100 and a population standard deviation of 15. Take 10 random samples of size 25 and calculate a 90% confidence interval for each.
• Observations:• 9 of the samples resulted in
__________________________________
• One was a _____________ (__) and __________________________________
Example: Narrower Intervals
• Scenario: A 95% confidence interval for the mean SAT score for Pitt students was (1173.56, 1326.44).
• Question: Keeping all other statistics the same, which of the following will result in a narrower confidence interval?
• Choices:I. Using 90% confidence
II. Using a population standard deviation of 300
III. Using a sample size of 50
• Answer: _________________________I. Critical value would have been ______________
II. More variability in population creates ____________________ in the interval
III. More information helps create a _____________________ interval estimate
Factors Leading to Narrower Intervals
• Question: How can a confidence interval for the population mean become narrower?
!̅ ± / ⁄9 :
$
;
• Answer:• Decrease confidence level
• Decrease standard deviation
• Increase sample size
• Question: Why would we want a narrower interval?
• Answer: Provides a _____________________________ of the parameter• Note: Making an interval narrower by reducing the confidence level
comes with the drawback of __________________________.
Sample Size Calculation
• In many fields, it is known ahead of time how wide a confidence interval is allowed to be. Researchers may need to know how large a sample is necessary to attain that width.
• Given a level of confidence 100 1 − ( % and a population standard deviation $, the sample size necessary to attain a margin of error = is:
; =/ ⁄9 :$
=
:
• Round up to next largest integer if ; is a decimal
Reminder: The margin of error is half the width of the confidence interval.
Example: Sample Size Calculation
• Scenario: A random sample of the heights of 21 men found a sample mean of 70.6 inches. Assume the population standard deviation is 4 inches.
• Question: How large a sample would be needed to reduce the width of the 99% confidence interval to 1.5 inches?
70.668.35 72.85
_______ _______70.6
Width: _____ in. Margin of Error: _____ in.
Original Interval
Width: 4.5 inches
Sample Size: 21
New Interval
Width: 1.5 inches
Sample Size: ?
Example: Sample Size Calculation
• Scenario: A random sample of the heights of 21 men found a sample mean of 70.6 inches. Assume the population standard deviation is 4 inches.
• Question: How large a sample would be needed to reduce the width of the 99% confidence interval to 1.5 inches?
• Answer:• Margin of Error: ______________________
• Critical Value: ______ confidence à ___________________
• Sample Size: ______________________________________________________
• Round up to _______ people