Fiveable
Fiveable
pep
Fiveable
Fiveable

or

Log in

Find what you need to study


Light

7.7 Justifying a Claim About the Difference of Two Means Based on a Confidence Interval

3 min readjanuary 5, 2023

Jed Quiaoit

Jed Quiaoit

Josh Argo

Josh Argo

Jed Quiaoit

Jed Quiaoit

Josh Argo

Josh Argo

As you recall from Unit 7.3, a statistical claim is any belief that any population is equal (or not equal) to a given number or proportion. In dealing with two populations, our statistical claim is generally regarding whether these two populations are the same or different. Our null statistical claim when dealing with two different populations is that they are not different. In other words, their means are the same. 🐟

Making a Conclusion

When given a and making a conclusion, there is a preset template that we can use that helps us to be sure to include all of the vocabulary necessary to score well on the AP Statistics exam. 📙

Template

Our template should go as follows:

  • "We are ___% confident that the true difference in between _______ and _______ (context of problem) is (___, ___).

  • "In repeated random sampling with the same , approximately C% of confidence intervals created will capture the difference of (add more about context).

As with any AP Statistics Free Response question, it is always imperative that your answer includes context of the problem given. After all, a comprehensive interpretation for a for the difference of two should include a reference to the samples taken and details about the populations they represent.

When testing for the difference in two populations, it is also important to use that interval to test the claim that the two populations are the same. If the two populations are statistically "the same," 0 will be included in your interval. If after completing your interval, you do not have 0 in your interval, there is reason to believe that your two populations do, in fact, have different means.

Finishing Our Apples to Apples Example

Let's finish our example with the green apples and red apples. 🍏🍎

In Unit 7.5, we concluded that our for the difference in our two color apples was (0.408, 0.592). Our conclusion should go as follows:

"We are 95% confident that the true difference in the of the weights of green apples and red apples is between (0.408, 0.592). Since 0 is not included in our interval, we have significant evidence that the weights of green apples and red apples are in fact different."

Notice since 0 was not in our interval, that tells us, with 95% confidence, that there is some sort of difference in our two .

https://cdn.pixabay.com/photo/2016/04/02/09/43/apple-1302430_960_720.jpg

image courtesy of pixabay

Relating Confidence Intervals and Sample Sizes

When all other things remain the same, the width of the for the difference of two means tends to decrease as the sample sizes increase. That's right: the width of the for the difference of two means (also known as the ) is inversely proportional to the .

Recall that the represents the range of values within which the true population parameter is likely to fall, with a certain level of confidence. In the case of the difference of two means, the is calculated by taking the difference between the two sample means and adding and subtracting the . The is calculated based on the of the difference between the means and the desired level of confidence.

Increasing the allows for a more precise estimate of the population parameter, which results in a narrower confidence interval and a smaller .

https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2F-crhth4mJQdpX.png?alt=media&token=da086f8a-5f5a-4cbb-88fc-f5654dbfe850

Source: Medium

🎥 Watch: AP Stats - Inference: Confidence Intervals for Means

Key Terms to Review (6)

Confidence Interval

: A confidence interval is a range of values that is likely to contain the true value of a population parameter. It provides an estimate along with a level of confidence about how accurate the estimate is.

Confidence Level

: Confidence level refers to how confident we are that our interval estimate contains or captures the true population parameter. It represents our degree of certainty or reliability in estimating this parameter.

Margin of Error

: The margin of error is a measure of the uncertainty or variability in survey results. It represents the range within which the true population parameter is likely to fall.

Population Means

: Population means refer to the average value of a specific characteristic or variable in an entire population.

Sample Size

: The sample size refers to the number of individuals or observations included in a study or experiment.

Standard Error

: The standard error is a measure of the variability or spread of sample means around the population mean. It tells us how much we can expect sample means to differ from the true population mean.

7.7 Justifying a Claim About the Difference of Two Means Based on a Confidence Interval

3 min readjanuary 5, 2023

Jed Quiaoit

Jed Quiaoit

Josh Argo

Josh Argo

Jed Quiaoit

Jed Quiaoit

Josh Argo

Josh Argo

As you recall from Unit 7.3, a statistical claim is any belief that any population is equal (or not equal) to a given number or proportion. In dealing with two populations, our statistical claim is generally regarding whether these two populations are the same or different. Our null statistical claim when dealing with two different populations is that they are not different. In other words, their means are the same. 🐟

Making a Conclusion

When given a and making a conclusion, there is a preset template that we can use that helps us to be sure to include all of the vocabulary necessary to score well on the AP Statistics exam. 📙

Template

Our template should go as follows:

  • "We are ___% confident that the true difference in between _______ and _______ (context of problem) is (___, ___).

  • "In repeated random sampling with the same , approximately C% of confidence intervals created will capture the difference of (add more about context).

As with any AP Statistics Free Response question, it is always imperative that your answer includes context of the problem given. After all, a comprehensive interpretation for a for the difference of two should include a reference to the samples taken and details about the populations they represent.

When testing for the difference in two populations, it is also important to use that interval to test the claim that the two populations are the same. If the two populations are statistically "the same," 0 will be included in your interval. If after completing your interval, you do not have 0 in your interval, there is reason to believe that your two populations do, in fact, have different means.

Finishing Our Apples to Apples Example

Let's finish our example with the green apples and red apples. 🍏🍎

In Unit 7.5, we concluded that our for the difference in our two color apples was (0.408, 0.592). Our conclusion should go as follows:

"We are 95% confident that the true difference in the of the weights of green apples and red apples is between (0.408, 0.592). Since 0 is not included in our interval, we have significant evidence that the weights of green apples and red apples are in fact different."

Notice since 0 was not in our interval, that tells us, with 95% confidence, that there is some sort of difference in our two .

https://cdn.pixabay.com/photo/2016/04/02/09/43/apple-1302430_960_720.jpg

image courtesy of pixabay

Relating Confidence Intervals and Sample Sizes

When all other things remain the same, the width of the for the difference of two means tends to decrease as the sample sizes increase. That's right: the width of the for the difference of two means (also known as the ) is inversely proportional to the .

Recall that the represents the range of values within which the true population parameter is likely to fall, with a certain level of confidence. In the case of the difference of two means, the is calculated by taking the difference between the two sample means and adding and subtracting the . The is calculated based on the of the difference between the means and the desired level of confidence.

Increasing the allows for a more precise estimate of the population parameter, which results in a narrower confidence interval and a smaller .

https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2F-crhth4mJQdpX.png?alt=media&token=da086f8a-5f5a-4cbb-88fc-f5654dbfe850

Source: Medium

🎥 Watch: AP Stats - Inference: Confidence Intervals for Means

Key Terms to Review (6)

Confidence Interval

: A confidence interval is a range of values that is likely to contain the true value of a population parameter. It provides an estimate along with a level of confidence about how accurate the estimate is.

Confidence Level

: Confidence level refers to how confident we are that our interval estimate contains or captures the true population parameter. It represents our degree of certainty or reliability in estimating this parameter.

Margin of Error

: The margin of error is a measure of the uncertainty or variability in survey results. It represents the range within which the true population parameter is likely to fall.

Population Means

: Population means refer to the average value of a specific characteristic or variable in an entire population.

Sample Size

: The sample size refers to the number of individuals or observations included in a study or experiment.

Standard Error

: The standard error is a measure of the variability or spread of sample means around the population mean. It tells us how much we can expect sample means to differ from the true population mean.


© 2024 Fiveable Inc. All rights reserved.

AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.


© 2024 Fiveable Inc. All rights reserved.

AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.