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3 years ago

For the function f(x) = |2x-7| - 3 find f(2)

2 answers:

8 0

Evaluate abs(2 x - 7) - 3 where x = 2:abs(2 x - 7) - 3 = abs(2 2 - 7) - 3
2×2 = 4:abs(4 - 7) - 3
4 - 7 = -3:abs(-3) - 3
Since -3<=0, then abs(-3) = 3:3 - 3
3 - 3 = 0:Answer: 0

Grace [21]3 years ago

6 0

F(x)=[2x-7] -3
f(2)=[2(2)-7]-3
f(2)=[4-7]-3
f(2)=[-3]-3
f(2)= 3 -3 Remember absolute value is the distance from zero. No number will ever have a negative absolute value! :)
f(2)= 0

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A retailer ordered a combination of 50 black and white sweatshirts. Each white sweatshirt cost him $10 and

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Simultaneous equation :brainly.com/question/12919422

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Andrew plans to retire in 32 years. He plans to invest part of his retirement funds in stocks, so he seeks out information on pa

Debora [2.8K]

Answer:

a) 0.0885 = 8.85% probability that the mean annual return on common stocks over the next 40 years will exceed 13%.

b) 0.4129 = 41.29% probability that the mean return will be less than 8%

Step-by-step explanation:

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

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, 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 $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean 8.7% and standard deviation 20.2%.

This means that $\mu = 8.7, \sigma = 20.2$

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This means that $n = 40, s = \frac{20.2}{\sqrt{40}}$

(a) What is the probability (assuming that the past pattern of variation continues) that the mean annual return on common stocks over the next 40 years will exceed 13%?

This is 1 subtracted by the pvalue of Z when X = 13. So

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

By the Central Limit Theorem

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