In this video I'm going to go over question 11 you see we are given the following data table with chest size in inches and weight in pounds the first part of the question says to what is says what is the regression equation round to one decimal place as needed so I'm going to open up our data in statcrunch.

Going to run simple linear for our regression analysis.

RX variable is chastise.

Why variable is weight.

Hornet computer.

See we are given the slope.

Is 11.1 or intercept is -172.6.

Notice your Y intercept in this format comes first and then your slope come seconds when you're in putting it in the equation your slope is going to be right next to your ex variable.

The next part of the question says what is the best protected with predicted weight of a bear with a chest size of 51 in so I'm going to go back to our module 6 learning guide and we have the following strategy for predicting values of Y.

Notice what it what we do to determine which strategy is to see if I were aggression equation is a good model or not so we're going to need to go back into our statcrunch analysis and look at R P value.

So if I look at my P value associated with my slope we can look at this as .03 12 right here.

You could also see there's a pizza same P value associated with the model so that's .03 12 that is a small P value but let's see what are given significance level as our significance level of 5 so since R P value of pointer 3 or 3% of smaller than 5% we are going to reject that null hypothesis and that means our regression equation is a good model so we can use that model to find our predictive value.

So according to the strategy this is the way we're going to do this we can use statcrunch to be a little bit more accurate than if we just type it in so that's what I'm going to do please note that if our p-value was larger than our significance level are regression equation is not a good model so the best predicted value would be the meaning of all the Y value so we would need to find that average of all the Y values what you could calculate By Hand by adding up all your y values dividing by the total or you could use your summary statistics in statcrunch to run that analysis.

So I'm going to go back into this edit.

And again our skins levels .05 so the chest size that they want us to find the best predicted wait for is 51.

So I could go down here.

And I can input in 51.

AR level is .95 which is correct cuz 1 - 2.05 is going to give us .95 and then I'm going to hit computer.

If we scroll down we can now see this predicted value for Y which would be 392.447.

And how I did that it went back into my simple linear regression analysis.

The x value is 51 our significance level was .05 so our level of confidence is going to be one mind as that which is 295 and then I hit.

We want to round to one decimal place.

So that would be 392.4.

Now like I said Lori if your P value is larger than your significance level to find that best predicted value we would find the average of r y value so real quick I'm going to show you that.

Are the stats summary statistics columns are y value in this case is going to be alright.

Wait.

Choosing the way column and then I'm choosing to find the mean or the average and I hit computer.

You can see that mean if we were using that for answer because we noticed our p-value was larger than our significance level and we could not use our equation then it would be 353.7 if we round to one decimal places again you can just add up those y-values by hand and in this case we had.

1 2 3 4 5 6 different value so you would add those up and divided by 6 and that would also give you the man or the average.

Now for the last part of this question is says it's the result close to the actual weight of 422.

The best answer is going to be the this result is not very close to the actual weight of the bear.

So continue to ask questions when you have them and have a great day.