Calculating Margin of Error for 95% Confidence Interval in Rent Predictions

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In summary, to capture the actual Rent amount 95% of the time, predictions from the fitted equation should include a margin of error of about plus or minus $114 (rounded to the nearest ten dollars). This can be calculated by taking 2 times the standard error, which can be found using the formula shown in the table provided in the link. This is an inference for regression test, as indicated by the discussion and resources provided.
  • #1
rowdy3
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To capture the actual Rent amount 95% of the time, predictions from the fitted equation should include a margin of error of about plus or minus ______ (round to the nearest ten dollars).
$128
$114 (answer)
$57
$228
Here's a pic of the table. How did they get the answer? http://picturetrail.com/sfx/album/view/24285022
I know k2= 95%. I know you do 2 * (standard error) but I don't see that on the table.
 
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  • #2
Is this an inference for regression test that you're doing?
 
  • #3
Yes I think so.
 
  • #4
Check out :

http://www.stat.berkeley.edu/~thornton/STAT20/lec18slides4.pdf

focus on pages 3,4, and let us know if you need more help.
 
  • #5
Please let me know if you need more help.
 

FAQ: Calculating Margin of Error for 95% Confidence Interval in Rent Predictions

What does "Stat Help" mean?

"Stat Help" is a shortened term for "statistical help." It refers to any assistance or guidance provided in regards to statistical analysis or interpretation of data.

What is the significance of K2 in statistical analysis?

K2 is a measure of statistical significance, specifically the level of confidence that can be placed on the results of a statistical test. A K2 value of 95% indicates that there is a 95% chance that the results are not due to chance and can be considered reliable.

How is the confidence level of 95% determined in statistical analysis?

The confidence level of 95% is determined by calculating the standard error of the mean and using it to construct a confidence interval. This interval represents the range of values within which the true population mean is likely to fall with 95% certainty.

What is the difference between statistical significance and practical significance?

Statistical significance refers to the likelihood that the results of a statistical test are not due to chance. Practical significance, on the other hand, refers to the real-world or practical importance of the results. A finding may be statistically significant but not practically significant, and vice versa.

How can I use a confidence level of 95% in my research or analysis?

A confidence level of 95% is commonly used in research and analysis to determine the reliability of results. It can help to determine if there is a significant difference between groups, if a relationship exists between variables, or if a particular intervention or treatment has an effect. It is important to note that a confidence level of 95% does not guarantee the accuracy of the results, but it provides a high level of confidence in the findings.

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