For a project to qualify for carbon credits, the required precision of estimates of the amount of wood saved per new stove adopted is 90/10. In other words, the margin of error of a 90% confidence interval can be no more than 10% of the value of the sample statistic. Will the data from the pilot study enable this project to qualify for carbon credits?

Step-by-step explanation:

The required estimate is

90 woods saved by 10 new stoves adopted

Hence the required estimate is 9 woods saved per new stove adopted.

Data from the pilot study will enable this project to qualify for carbon credits if we are 90% confident that the data values from the pilot study fall within [8.1 - 9.9] woods saved per new stove adopted.

The lower and upper limits are derived from the margin of error, which is 10%.

9-0.9 = 8.1

9+0.9 = 9.9

On the other hand, if less than 90% of the values from the pilot study fall within this range, then the data from the study will no enable the project to qualify for carbon credits.

no oblique asymptote

step-by-step explanation:

to find the oblique asymptote of f(x)

here numerator has degree 1 and denomintor degree 2

degree of numerator < degree of denominator

hence there is no oblique asymptote

when the degree of the denominator > that of the numerator, we saw that the value in the denominator got so much bigger, so quickly,   giving us a horizontal asymptote of the x-axis. or we can write

f(x) = a polynomial of x + a proper fraction.

in this case only we have oblique asymptotes but not when numerator has less degree.

10 - 8 = -2

  8 - 6 = -2

etc, so -2 is the common difference

step-by-step explanation: