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Instructions to question: Construct a scatterplot, find the value of the linear

ID: 2951403 • Letter: I

Question

   Instructions to question:                                       Construct a scatterplot, find the value of the linear correlationcoefficient r, find the critical value of r from table A-6 by using= 0.05, and determine whether there is a linear correlationbetween the two variables.    Question: Listed below are the numbers of fires (in thousands) and the acres that were burned (in millions) in 11Western states in each year of the last decade. Is there acorrelation?.The data were listed under a headline of "Loggersseize on fires to argue for more cutting". Do the data support theargument that as loggers remove more trees, the risk of firedecreases because the forests are less dense? Fires: 73 69   58  48   .84    62 57  45 70 63   48 Acres: 6.2 4.2  1.9 2.7    5.0   1.6  3.0 1.6   1.5 2.0 3.7 Need some help on this one please. burned    Instructions to question:                                       Construct a scatterplot, find the value of the linear correlationcoefficient r, find the critical value of r from table A-6 by using= 0.05, and determine whether there is a linear correlationbetween the two variables.    Question: Listed below are the numbers of fires (in thousands) and the acres that were burned (in millions) in 11Western states in each year of the last decade. Is there acorrelation?.The data were listed under a headline of "Loggersseize on fires to argue for more cutting". Do the data support theargument that as loggers remove more trees, the risk of firedecreases because the forests are less dense? Fires: 73 69   58  48   .84    62 57  45 70 63   48 Acres: 6.2 4.2  1.9 2.7    5.0   1.6  3.0 1.6   1.5 2.0 3.7 Need some help on this one please. burned

Explanation / Answer

this can be determined by your calculator, or if you have tocalculate manually: r = [sum of ((x-xmean)(y-ymean))] /[(x-xmean)^2(y-ymean)^2] on the calculator, under the data presented for LinReg(ax+b),the r for this problem is given as r = 0.517 if r is near 1, then there is a strong positive linearcorrelation between the variables if r is near 0, then there is weak if any linear correlationbetween the variables