Answer: option D is the correct answer.
Step-by-step explanation:
The given sequence is a geometric sequence because the consecutive terms differ by a common ratio.
The formula for determining the nth term of a geometric progression is expressed as
an = a1r^(n - 1)
Where
a1 represents the first term of the sequence.
r represents the common ratio.
n represents the number of terms.
From the information given,
a1 = 36
r = 12/36 = 4/12 = 1/3
Therefore, the formula for the nth term of the sequence is
an = 36 × 1/3^(n - 1)
an = 36 × 3^-1(n - 1)
an = 36 × 3^(-n + 1)
an = 36 × 3^(1 - n)
Answer:
1. 4
2. 9
3. <
Step-by-step explanation:
The ratio 4 to 5 means that the left model should have 4 segments shaded (out of 5 given).
The ratio 9 to 10 means that the right model should have 9 segments shaded (out of 10 given).
Compare the shaded regions. If you draw the horizontal line in the left model. then there will be 8 segments shaded (out of 10), this means the ratio 4 : 5 is less than the ratio 9 : 10.
Answer:
total amount donated when aaron walks n miles = $2 + $3(n-1)
Step-by-step explanation:
Aaron participates in a walkathon for charity. He has a sponsor who has pledged a base donation of $2 for the first mile he walks and then a certain dollar amount for each additional mile he walks. Based on this pledge, if Aaron walks 8 miles, the sponsor will donate a total of $23 to the charity.
Write a formula that can be used to determine the amount of money this sponsor donates when Aaron walks n miles.
total amount sponsor pays = base donations + (additional miles walked after first mile x amount paid)
when Aaron walks 8 miles
additional miles = 8 - 1 = 7
23 = 2 + 7x
23 - 2 = 7x
x = 3
additional amount paid is $3
total amount donated when aaron walks n miles = $2 + $3(n-1)
Answer:
(B) (0.396, 1.712)
Step-by-step explanation:
From the information given;
Confidence Interval = 0.95
Significance Level 
The confidence interval for regression coefficient beta (whereby in this case it is the coefficient of the diameter) is expressed by:
= 
From the regression coefficient, the estimated value of beta^ = 1.054
