Simplify (18+t)(-3)+9

Write a rule for the nth term of the arithmetic sequence 3, 11, 19, 27, 35... what is a20?

vladimir1956 [14]

3, 11, 19, 27, 35...

a = 3
d = 11-3 = 8
a20 = a + 19d = 3 + 19*8 = 3 + 132 = 135

HOPE IT HELPS!

5 0

2 years ago

If 18 plums weigh 54 ounces, then 6 plums weigh how many<br> ounces?

Debora [2.8K]

Answer:

18

Hope this helps :) Please mark this brainiest?

Step-by-step explanation:

18/6=3

54/3=18

8 0

2 years ago

Read 2 more answers

Please help!!!! <br><br> If f(1) = 2 and f(n+1) = f(n)^2 – 3 then find the value of f(3).

Black_prince [1.1K]

Answer:

The value of f(3) is -2.

Step-by-step explanation:

This is a recursive function. So

$f(1) = 2$

Now, we find f(2) in function of f(1). So

$f(1+1) = f(1)^2 - 3$

$f(2) = f(1)^2 - 3 = 2^2 - 3 = 1$

Now, with f(2), we can find the value of f(3).

$f(2+1) = f(2)^2 - 3$

$f(3) = f(2)^2 - 3 = 1^2 - 3 = -2$

The value of f(3) is -2.

4 0

3 years ago

A population has a mean of 200 and a standard deviation of 50. Suppose a sample of size 100 is selected and x is used to estimat

zmey [24]

Answer:

a) 0.6426 = 64.26% probability that the sample mean will be within +/- 5 of the population mean.

b) 0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .