Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 525 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 226264-366-470-539-

Crash Fatality Rate 16 157 15.4 15.3 15

The equation of regression is

The predicted crash fatality rate is 15.057 for 525 metric tons of lemon import.

Step-by-step explanation:

We are given the following lemon/crash data,

Lemon Imports = 226 264 366 470 539

Crash Fatality Rate = 16 15.7 15.4 15.3 15

The regression equation is given by

where x is the lemon imports in metric tons and y is the fatality rate per 100,000 people.

The constants b is the slope and a is the y-intercept of the regression line and are given by

Using Excel to find

= 1865

= 77.4

= 28673.2

= 766149

So the constants a and b are

Therefore, the equation of regression is

The best predicted crash fatality rate for a year in which there are 525 metric tons of lemon imports is given by

The predicted crash fatality rate of 15.057 for 525 metric tons of lemon import seems to be satisfactory since it lies between the crash fatality rate of 15 to 15.3 for lemon imports of 539 to 470.

= 5

step-by-step explanation:

to find the 15th term substitute n = 15 into the nth term formula

= (- 3 × 15 ) + 50 = - 45 + 50 = 5

step-by-step explanation:

consider an orange peel: if you want to try and lay it flat, you have to stretch it, we know exactly how things are being stretched or squashed at any given point. we have many different map projections because each has different patterns of some projections can even preserve certain features of the earth without