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Hey there, welcome to numerary.
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We are given data values below and we're asked to find the regression line.
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So we had to calculate the values including the mean and the sum and the sum of squares to find the regression equation.
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So this is the format that they want to make us writing.
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Y equals bx, so b is the slope plus a is our intercept.
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So we had to find b and we have to find a.
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So let's find our values here.
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So first up, we have to find the means of both x and y.
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So x bar is mean of x, and x, well, y bar is mean of y bar.
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It's mean of y.
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So let's see what we have here.
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So let's find the mean of x first.
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So we're going to take this sum.
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So we add all the numbers equals 33, divided by.
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Let's take a bar here in line.
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Divided by our total number of values.
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So the total number of values here, it looks like it's around, i think, six numbers.
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So divided by six, and we get x bar of 5 .5.
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We're gonna do the same for y.
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So our sum for y is 71 .1 divided by six.
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We get a mean for y around 11 .84.
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Now with these, these, means over here, we can find the sum of squares of x.
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Sum of squares of x is basically the equation is the sum, the sum of x minus this mean, so of 5 .5 squared.
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We would get a sum of squares of x of around 17 .5, and we can calculate our sum of products.
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Some of products is basically the sum of x minus the mean, multiplied by y minus the mean...