Week 6: LEO Discussion Topic

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Choose either topic 1 or topic 2 for your initial post. Respond to either for your peer reply post.
 

Topic 1:
Results from surveys or opinion polls often report a range of values—the sample statistic plus or minus a margin of error (the resulting range is called a confidence interval). This tells us that the range is likely to contain the population parameter. How much wiggle room we provide is based on how much confidence we wish to have that the range contains the actual population mean. That confidence level is directly related to the middle "truth" area we will accept versus the dubious tail area we will reject—also known as alpha (α). The more confidence we wish to have—the more middle ground we will need to accept (more wiggle room)—thus a smaller tail area. If we insist on a larger alpha (more dubious tail area), we narrow the middle ground we will accept and thus provide less wiggle room—so the more likely it is that we will miss the true average (and, thus, we have a lower confidence level). A 95% confidence level leaves 5% alpha. A 99% confidence level leaves 1% alpha.

Now, without calculating a mean or margin of error or a confidence level, provide an example from your current (or your future) professional or personal life that describes a measurement that is normal—and how much wiggle room on either side would be appropriate. When would you want a 95% confidence interval, and when would you want a 99% confidence level (a little more wiggle room—so a wider range)? This serves as your initial post to the discussion (if you choose topic 1) and is due by 11:59 p.m. EST on Saturday.
 
-OR-
 

Topic 2:
Two or more samples are often compared when we suspect that there are differences between the groups—for example, are cancer rates higher in one town than another, or are test scores higher in one class than another? In your chosen field, when might you want to know the mean differences between two or more groups? Please describe the situation (what groups, what measurements) including how and why it would be used. This serves as your initial post to the discussion (if you choose topic #2) and is due by 11:59 p.m. EST on Saturday.

Week 6: LEO Discussion Topic

Subscribe

Choose either topic 1 or topic 2 for your initial post. Respond to either for your peer reply post.
 

Topic 1:
Results from surveys or opinion polls often report a range of values—the sample statistic plus or minus a margin of error (the resulting range is called a confidence interval). This tells us that the range is likely to contain the population parameter. How much wiggle room we provide is based on how much confidence we wish to have that the range contains the actual population mean. That confidence level is directly related to the middle "truth" area we will accept versus the dubious tail area we will reject—also known as alpha (α). The more confidence we wish to have—the more middle ground we will need to accept (more wiggle room)—thus a smaller tail area. If we insist on a larger alpha (more dubious tail area), we narrow the middle ground we will accept and thus provide less wiggle room—so the more likely it is that we will miss the true average (and, thus, we have a lower confidence level). A 95% confidence level leaves 5% alpha. A 99% confidence level leaves 1% alpha.

Now, without calculating a mean or margin of error or a confidence level, provide an example from your current (or your future) professional or personal life that describes a measurement that is normal—and how much wiggle room on either side would be appropriate. When would you want a 95% confidence interval, and when would you want a 99% confidence level (a little more wiggle room—so a wider range)? This serves as your initial post to the discussion (if you choose topic 1) and is due by 11:59 p.m. EST on Saturday.
 
-OR-
 

Topic 2:
Two or more samples are often compared when we suspect that there are differences between the groups—for example, are cancer rates higher in one town than another, or are test scores higher in one class than another? In your chosen field, when might you want to know the mean differences between two or more groups? Please describe the situation (what groups, what measurements) including how and why it would be used. This serves as your initial post to the discussion (if you choose topic #2) and is due by 11:59 p.m. EST on Saturday.

Week 6: LEO Discussion Topic

Subscribe

Choose either topic 1 or topic 2 for your initial post. Respond to either for your peer reply post.
 

Topic 1:
Results from surveys or opinion polls often report a range of values—the sample statistic plus or minus a margin of error (the resulting range is called a confidence interval). This tells us that the range is likely to contain the population parameter. How much wiggle room we provide is based on how much confidence we wish to have that the range contains the actual population mean. That confidence level is directly related to the middle "truth" area we will accept versus the dubious tail area we will reject—also known as alpha (α). The more confidence we wish to have—the more middle ground we will need to accept (more wiggle room)—thus a smaller tail area. If we insist on a larger alpha (more dubious tail area), we narrow the middle ground we will accept and thus provide less wiggle room—so the more likely it is that we will miss the true average (and, thus, we have a lower confidence level). A 95% confidence level leaves 5% alpha. A 99% confidence level leaves 1% alpha.

Now, without calculating a mean or margin of error or a confidence level, provide an example from your current (or your future) professional or personal life that describes a measurement that is normal—and how much wiggle room on either side would be appropriate. When would you want a 95% confidence interval, and when would you want a 99% confidence level (a little more wiggle room—so a wider range)? This serves as your initial post to the discussion (if you choose topic 1) and is due by 11:59 p.m. EST on Saturday.
 
-OR-
 

Topic 2:
Two or more samples are often compared when we suspect that there are differences between the groups—for example, are cancer rates higher in one town than another, or are test scores higher in one class than another? In your chosen field, when might you want to know the mean differences between two or more groups? Please describe the situation (what groups, what measurements) including how and why it would be used. This serves as your initial post to the discussion (if you choose topic #2) and is due by 11:59 p.m. EST on Saturday.