Which relation is NOT a function? Explain your answer.

If g(x) = x^2 - 4 find g (5) A. 6 B. 14 C. 21 D. 29

Marrrta [24]

C.21

5^2-4=21

Explanation

3 0

3 years ago

what are the steps to answer this question? Jeff is baking a cake. The recipe says that he has to mix 32 grams of powder to the

Deffense [45]

Well what I would do first is to divide 128 by 32 which I do believe gets you 4. So now you know that 1 cup of powder can make 4 servings. So you now know that each serving only requires 1/4 cup of the powder.

So now we know Jeff went over so now we have Jeff added 2/3 and he only needs 1/4. I would now make them both equivalent by multiplying the numerator and denominator of 2/3 by 4 and the same for 1/4 but instead by 4 multiply it by 3 which you would get 2/3=8/12 and 1/4=3/12. Now subtract the two to get your answer.

8/12-3/12=5/12

Answer: He went over and he needs to remove 5/12 of the cup

5 0

2 years ago

The problem is in the picture

Nitella [24]

The problem is the number by the side

7 0

2 years ago

Rockwell hardness of pins of a certain type is known to have a mean value of 50 and a standard deviation of 1.8. (Round your ans

Alenkinab [10]

Answer:

a) 0.011 = 1.1% probability that the sample mean hardness for a random sample of 17 pins is at least 51

b) 0.0001 = 0.1% probability that the sample mean hardness for a random sample of 45 pins is at least 51

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 normally distributed samples are solved using 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 $s = \frac{\sigma}{\sqrt{n}}$ .