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All right.
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So what i did here was in l1, i entered my temperature, and in l2, i entered the number of chirps.
00:07
And then i went to and ran linear regression a plus bx, with l1 and l2 being my x and y list.
00:17
So stat calculations.
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There's two linear regression options.
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It really doesn't matter which one you choose.
00:23
In stats, we typically put the y intercept first, so that's the one i chose.
00:26
And when we do that, we get our lee squares regression line negative 0 .30914 plus 1 .211925x.
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Or if we do it in context, the predicted number of chirps is equal to 0 .30914 plus 0 .21925 times the temperature.
00:53
So that was part a...