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Confidence Intervals Chapter 10 and 11

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Confidence Intervals. Chapter 10 and 11. Rate your confidence 0 - 100. Name my age within 10 years? within 5 years? within 1 year? Shooting a basketball at a wading pool, will make basket? Shooting the ball at a large trash can, will make basket? - PowerPoint PPT Presentation

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Page 1: Confidence Intervals

Confidence Intervals

Chapter 10 and 11

Page 2: Confidence Intervals

Rate your confidenceRate your confidence0 - 1000 - 100

• Name my age within 10 years?• within 5 years?• within 1 year?

• Shooting a basketball at a wading pool, will make basket?

• Shooting the ball at a large trash can, will make basket?

• Shooting the ball at a carnival, will make basket?

Page 3: Confidence Intervals

What happens to your confidence as the interval gets smaller?

The larger your confidence, the wider the interval.

Page 4: Confidence Intervals

Point Estimate

• Use a singlesingle statistic based on sample data to estimate a population parameter

• Simplest approach

• But not always very precise due to variationvariation in the sampling distribution

Page 5: Confidence Intervals

Confidence intervalsConfidence intervals

• Are used to estimate the unknown population mean

• Formula:

estimate + margin of error

Page 6: Confidence Intervals

Margin of errorMargin of error

• Shows how accurate we believe our estimate is

• The smaller the margin of error, the more precisemore precise our estimate of the true parameter

• Formula:

statistic theof

deviation standard

value

criticalm

Page 7: Confidence Intervals

Confidence levelConfidence level

• Is the success rate of the method used to construct the interval

• Using this method, ____% of the time the intervals constructed will contain the true population parameter

Page 8: Confidence Intervals

What does it mean to be 95% What does it mean to be 95% confident?confident?

• 95% chance that is contained in the confidence interval

• The probability that the interval contains is 95%

• The method used to construct the interval will produce intervals that contain 95% of the time.

Page 9: Confidence Intervals

• Found from the confidence level• The upper z-score with probability p lying to its

right under the standard normal curve

Confidence level tail area z*

.05 1.645

.025 1.96

.005 2.576

Critical value (z*)Critical value (z*)

.05

z*=1.645

.025

z*=1.96

.005

z*=2.57690%95%99%

Page 10: Confidence Intervals

Confidence interval for a Confidence interval for a population mean:population mean:

n

zx

*

estimate

Critical value

Standard deviation of the statistic

Margin of error

Page 11: Confidence Intervals

ActivityActivity

Page 12: Confidence Intervals

Steps for doing a confidence Steps for doing a confidence interval:interval:

1) Assumptions –• SRS from population

• Sampling distribution is normal (or approximately normal)

• Given (normal)

• Large sample size (approximately normal)

• Graph data (approximately normal)

• is known

2) Calculate the interval

3) Write a statement about the interval in the context of the problem.

Page 13: Confidence Intervals

Statement: Statement: (memorize!!)(memorize!!)

We are ________% confident that the true mean context lies within the interval ______ and ______.

Page 14: Confidence Intervals

Assumptions:Have an SRS of blood measurementsPotassium level is normally distributed (given) known

We are 90% confident that the true mean potassium level is between 3.01 and 3.39.

A test for the level of potassium in the blood is not perfectly precise. Suppose that repeated measurements for the same person on different days vary normally with = 0.2. A random sample of three has a mean of 3.2. What is a 90% confidence interval for the mean potassium level?

3899.3,0101.33

2.645.12.3

Page 15: Confidence Intervals

Assumptions:Have an SRS of blood measurementsPotassium level is normally distributed (given) known

We are 95% confident that the true mean potassium level is between 2.97 and 3.43.

95% confidence interval?

4263.3,9737.23

2.96.12.3

Page 16: Confidence Intervals

99% confidence interval?

Assumptions:Have an SRS of blood measurementsPotassium level is normally distributed (given) known

We are 99% confident that the true mean potassium level is between 2.90 and 3.50.

4974.3,9026.23

2.576.22.3

Page 17: Confidence Intervals

What happens to the interval as the What happens to the interval as the confidence level increases?confidence level increases?

the interval gets wider as the confidence level increases

Page 18: Confidence Intervals

How can you make the margin of How can you make the margin of error smaller?error smaller?• z* smaller

(lower confidence level)

• smaller(less variation in the population)

• n larger(to cut the margin of error in half, n

must be 4 times as big)

Really cannot change!

Page 19: Confidence Intervals

A random sample of 50 FHS students was taken and their mean SAT score was 1250. (Assume = 105) What is a 95% confidence interval for the mean SAT scores of FHS students?

We are 95% confident that the true mean SAT score for FHS students is between 1220.9 and 1279.1

Page 20: Confidence Intervals

Suppose that we have this random sample of SAT scores:

950 1130 1260 1090 1310 1420 1190

What is a 95% confidence interval for the true mean SAT score? (Assume = 105)

We are 95% confident that the true mean SAT score for FHS students is between 1115.1 and 1270.6.

Page 21: Confidence Intervals

Find a sample size:Find a sample size:

n

zm

*

• If a certain margin of error is wanted, then to find the sample size necessary for that margin of error use:

Always round up to the nearest person!

Page 22: Confidence Intervals

The heights of FHS male students is normally distributed with = 2.5 inches. How large a sample is necessary to be accurate within + .75 inches with a 95% confidence interval?

n = 43

Page 23: Confidence Intervals

In a randomized comparative experiment on the effects of calcium on blood pressure, researchers divided 54 healthy, white males at random into two groups, takes calcium or placebo. The paper reports a mean seated systolic blood pressure of 114.9 with standard deviation of 9.3 for the placebo group. Assume systolic blood pressure is normally distributed.

Can you find a z-interval for this problem? Can you find a z-interval for this problem? Why or why not?Why or why not?

Page 24: Confidence Intervals

Student’s t- distributionStudent’s t- distribution

• Developed by William Gosset

• Continuous distribution

• Unimodal, symmetrical, bell-shaped density curve

• Above the horizontal axis

• Area under the curve equals 1

• Based on degrees of freedom

Page 25: Confidence Intervals

Graph examples of t- curves vs normal curve

Page 26: Confidence Intervals

How does How does tt compare to compare to normal?normal?• Shorter & more spread out

• More area under the tails

• As n increases, t-distributions become more like a standard normal distribution

Page 27: Confidence Intervals

How to find How to find tt**

• Use Table B for t distributions• Look up confidence level at bottom & df on

the sides• df = n – 1

Find these t*

90% confidence when n = 5

95% confidence when n = 15

t* =2.132

t* =2.145

Can also use invT on the calculator!

Need upper t* value with 5% is above – so 95% is below

invT(p,df)

Page 28: Confidence Intervals

Formula:Formula:

n

stx * :Interval Confidence

estimate

Critical value

Standard deviation of statistic

Margin of errorMargin of error

Page 29: Confidence Intervals

Assumptions for Assumptions for tt-inference-inference

• Have an SRS from population

• unknown

• Normal distribution– Given– Large sample size– Check graph of data

Page 30: Confidence Intervals

For the Ex. 4: Find a 95% confidence interval for the true mean systolic blood pressure of the placebo group.

Assumptions:

• Have an SRS of healthy, white males

• Systolic blood pressure is normally distributed (given).

• is unknown

We are 95% confident that the true mean systolic blood pressure is between 111.22 and 118.58.

)58.118,22.111(273.9

056.29.114

Page 31: Confidence Intervals

RobustRobust

• An inference procedure is ROBUST if the confidence level or p-value doesn’t change much if the assumptions are violated.

• t-procedures can be used with some skewness, as long as there are no outliers.

• Larger n can have more skewness.

Page 32: Confidence Intervals

Ex. 5 – A medical researcher measured the pulse rate of a random sample of 20 adults and found a mean pulse rate of 72.69 beats per minute with a standard deviation of 3.86 beats per minute. Assume pulse rate is normally distributed. Compute a 95% confidence interval for the true mean pulse rates of adults.

(70.883, 74.497)

Page 33: Confidence Intervals

Another medical researcher claims that the true mean pulse rate for adults is 72 beats per minute. Does the evidence support or refute this? Explain.

The 95% confidence interval contains the claim of 72 beats per minute. Therefore, there is no evidence to doubt the claim.

Page 34: Confidence Intervals

Ex. 6 – Consumer Reports tested 14 randomly selected brands of vanilla yogurt and found the following numbers of calories per serving:

160 200 220 230 120 180 140130 170 190 80 120 100 170

Compute a 98% confidence interval for the average calorie content per serving of vanilla yogurt.

(126.16, 189.56)

Page 35: Confidence Intervals

A diet guide claims that you will get 120 calories from a serving of vanilla yogurt. What does this evidence indicate?

Since 120 calories is not contained within the 98% confidence interval, the evidence suggest that the average calories per serving does not equal 120 calories.

Note: confidence intervals tell us if something is NOT EQUALNOT EQUAL

– never less or greater than!

Page 36: Confidence Intervals

Some Cautions:Some Cautions:

• The data MUST be a SRS from the population

• The formula is not correct for more complex sampling designs, i.e., stratified, etc.

• No way to correct for bias in data

Page 37: Confidence Intervals

Cautions continued:Cautions continued:

• Outliers can have a large effect on confidence interval

• Must know to do a z-interval – which is unrealistic in practice