## Generalize CI - Intro to Inferential Statistics

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Well, this value here is just a point. It's mu, which is what we already know,
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the mean clock score, 37.72 in our last example, plus 1.96. It doesn't really
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make sense to add a z score, so this value is not an interval and it doesn't
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even make sense. Here, we're getting a little closer because now we have an
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interval. But as I said before, it doesn't make sense to just subtract a z score
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because this is the number of standard deviations away from the mean, so we want
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to find the value along the x-axis for this interval. This one looks more
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promising. We have our sample mean. And we subtract 1.96 standard deviations,
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and since the standard deviation is sigma divided by root n that would be this
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value here, and then if we add 1.96 standard deviations that would give this
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value here. And that is our confidence interval. So, we found the answer. But
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let's explore this one anyway. This one we can't even figure out what it is
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because we don't know this population mean after the intervention. So, we're not
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able to compute this. If you selected this one, then you were pretty close. So,
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good job.
Title:
Generalize CI - Intro to Inferential Statistics
Description:

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Video Language:
English
Team:
Udacity
Project:
UD201 - Intro to Inferential Statistics
Duration:
01:18
 Udacity Robot edited English subtitles for 02-20 Generalize CI Udacity Robot edited English subtitles for 02-20 Generalize CI Udacity Robot edited English subtitles for 02-20 Generalize CI Udacity Robot edited English subtitles for 02-20 Generalize CI Cogi-Admin added a translation

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