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3 years ago

List all the factors of 16

Mathematics

2 answers:

DerKrebs [107]3 years ago

8 0

Ansnwer:

1, 2, 4, 8, 16

Step-by-step explanation:

and its Factors in Pairs are (1, 16), (2, 8), and (4, 4).

Olenka [21]3 years ago

5 0

Answer:

There are 5 factors of 16, which are 1, 2, 4, 8, and 16.

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4 years ago

Concerns about the climate change and CO2 reduction have initiated the commercial production of blends of biodiesel (e.g. from r

natta225 [31]

Answer:

a) 99% of the sample means will fall between 0.933 and 0.941.

b) By the Central Limit Theorem, approximately normal, with mean 0.937 and standard deviation 0.0015.

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 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 $s = \frac{\sigma}{\sqrt{n}}$ .

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

(a) If the true mean is 0.9370 with a standard deviation of 0.0090 within what interval will 99% of the sample means fail?

Samples of 34 means that $n = 34$

We have that $\mu = 0.937, \sigma = 0.009$

By the Central Limit Theorem, $s = \frac{0.009}{\sqrt{34}} = 0.0015$

Within what interval will 99% of the sample means fail?

Between the (100-99)/2 = 0.5th percentile and the (100+99)/2 = 99.5th percentile.

0.5th percentile:

X when Z has a pvalue of 0.005. So X when Z = -2.575.

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

By the Central Limit Theorem

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

$-2.575 = \frac{X - 0.937}{0.0015}$

$X - 0.937 = -2.575*0.0015$

$X = 0.933$

99.5th percentile:

X when Z has a pvalue of 0.995. So X when Z = 2.575.

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

$2.575 = \frac{X - 0.937}{0.0015}$

$X - 0.937 = 2.575*0.0015$

$X = 0.941$

99% of the sample means will fall between 0.933 and 0.941.

(b) If the true mean 0.9370 with a standard deviation of 0.0090, what is the sampling distribution of ¯X?

By the Central Limit Theorem, approximately normal, with mean 0.937 and standard deviation 0.0015.

6 0

3 years ago

A pizza parlor offers 3 sizes of pizzas, 2 types of crust, and one of 4 different toppings. How many different pizzas can be mad

KonstantinChe [14]

Answer: The total number of pizzas that can be made from the given choices is 24.

Step-by-step explanation: Given that a pizza parlor offers 3 sizes of pizzas, 2 types of crust, and one of 4 different toppings.

We are to find the number of different pizzas that can be made from the given choices.

We have the <em><u>COUNTING PRINCIPLE :</u></em>

If we have m ways of doing one task and n ways of doing the second task, then the number of ways in which we can do both the tasks together is m×n.

Therefore, the number of different pizzas that can be made from the given choices is

$N=3\times2\times4=24.$