Abotanist found a correlation between the length of an aspen leaf and its surface area to be 0.94. why does the correlation value of 0.94 not necessarily indicate that a linear model is the most appropriate model for the relationship between length of an aspen leaf and its surface area?

A correlation coefficient of +1 or -1 will indicate a direct linear model is the most appropriate but 0.94 shows that a very good direct correlation exists between the length of an aspen leaf and its surface area.

Step-by-step explanation:

this is because a values of r lying between +1 and −1, where +1 indicates perfect direct  correlation,−1 indicates perfect inverse correlation and 0 indicates that no correlation exists.

Between these values, the smaller the value of r, the less is the amount of correlation which exists. Generally, values of r in the ranges 0.7 to 1 and −0.7 to −1 show that a fair amount of correlation exists.

A correlation coefficient of 0.94 shows that a very good direct correlation exists between the length of an aspen leaf and its surface area but not necessarily indicate a linear model is the appropriate .

marco saved more.   he saved $35 more.

step-by-step explanation:

1+2+3+4+5+6+7+8+9+10 = 55

2*10 = 20

55-20 = 35

y = 2x

step-by-step explanation:

if you divide each number in the sequence, you'll see that they all have a multiple factor of 2. each number in the series, and any other numbers which may continue, will be multiplied by 2. therefore, y is the next number in the sequence, and x is the current one, so, our formula will be y = 2x.