Answer:
a. U(a) = 20000·0.9^a
b. about -$957 dollars per year
c. 13 years
Step-by-step explanation:
a) The age values are sequential, but the differences between "v" values are not constant. We suspect an exponential function. When we examine the ratios of adjacent table values, we find they are all 0.9, so the exponential function will be ...
U = (initial value)·(0.9^(age))
U(a) = 20000·0.9^a
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b) The average rate of change for the one year between age 7 and age 8 will be U(8) -U(7). A calculator evaluates that difference as -$956.59, about -$957.
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c) The car value drops by almost half in 6 years, so will drop by almost half of that in another 6 years. The car's age will be 12 or 13 years. A graph shows the age to be just over 13 years when the value is predicted to be $5000.
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A graphing calculator was used to evaluate the function and find the time associated with the given value. (See attached.) This is the "work" that was done to answer the questions.
The time to decrease to 1/4 of the original value can be found by solving ...
5000 = 25000·0.9^a
The solution is ...
a = log(.25)/log(0.9) ≈ 13.158 . . . . as found on the graph
Answer:
The average height of poodles in your kennel is 25.19 inches.
Step-by-step explanation:
This is a weighed average problem.
To find the weighed average, we sum each value of the set multiplied by it's weight, and then we divide by the sum of the weights.
In this problem, we have that:
Average 20.5 inches has weight 28.
Average 32.1 inches has weight 19.
What is the average height of poodles in your kennel?

The average height of poodles in your kennel is 25.19 inches.
The answer is the second one! He followed the customs himself :)
Answer:
Newspaper
Step-by-step explanation:
The level or degree of significance of independent variables used in a multiple regression analysis is usually measured by comparing the values of the slope Coefficient of each independent variable. From the result of the multiple regression analysis attached. The slope Coefficient of each independent variable is :
Television = 2.38 ; Newspaper = 1.45 and Mail = 1.82.
This slope values are the rate at which the dependent variable changes per unit increase in each of the independent variable.
Newapaper has the least slope Coefficient value of the 3 independent variables and hence will have the least significant effect on the value of revenue.