10. Simplify, (1/2^2/3 x 3^-2)
1 answer:
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Ok, so the question is based on geometric progression. Remember, the formula for calculating the nth-term of a geometric progression is: . The a in the expression stands for the 1st term of the sequence, and r is the common ratio of the elements of the sequence. Now let's take a look at the problem.
"A ping pong ball has a 75% rebound ration". We can infer that our common ratio, r, is 75% which is 0.75.
"When you drop it from a height of k feet...", this means the first height you drop it from, a.k.a, the first term.
Now going back to the expression, the nth-term = , we can substitute our common ration, 0.75 with r, and our 1st term, k, with a. This becomes:
. This becomes our expression.
a. The highest height achieved by the ball after six bounces. Our nth-term here is 6, so let's use our expression to find the 6th term.
b. The total distance travelled by the ball when it strikes the ground for the 12th time. This involves the use of the sum of elements in the geometric progression. The formula for that is , provided that r is less than 1, which it is in this case, since 0.75 is less than one. Our nth-term here is 12, so we substitute.
Answer:
a. 0.8366
b. No
Step-by-step explanation:
We will use the central limit theorem which can be applied to a random sample from any distribution as long as the mean and the variance are both finite and the sample size is large (the sample size n should be greater than 30). Here we have that the tip percentage at the restaurant has a mean value of 18% and a standard deviation of 6%, then because of the central limit theorem, we know that the sample mean tip percentage is approximately normally distributed with mean 18% and standard deviation .
a. The z-score related to 16% is given by (16-18)/0.9487 = -2.1081 and the z-score related to 19% is given by (19-18)/0.9487 = 1.0541. We are looking for
b. If the sample size had been 15 rather than 40, then, the probability requested in part (a) could not be calculated from the given information, this because the central limit theorem only applies when the sample size is large, for example n > 30.