All categories

3 years ago

F(x) = x + 2 when x = 10

Mathematics

2 answers:

murzikaleks [220]3 years ago

8 0

Answer:

f(10) = 12

Step-by-step explanation:

f(x) = x + 2

Substitute x for 10.

f(10) = 10 + 2

f(10) = 12

Doss [256]3 years ago

7 0

Answer:

Step-by-step explanation:

Substitute 10 into x -> 10+2=12

You might be interested in

Complete each sentence to describe the algebraic expression n + 2.35.

igor_vitrenko [27]

Step-by-step explanation:

variable is n

operation is addition

constant is 2.35

8 0

3 years ago

Read 2 more answers

84.7g of sugar is needed to make 11 cakes. How much sugar is needed for 5 cakes

Yuri [45]

Answer:

38.5 grams of sugar for 5 cakes

Step-by-step explanation:

Set up a ratio of grams to cakes

84.7g:11

How much for 1 cake(unit rate because you want sugar over cakes)?

Just divide by 11.

7.7g:1

But you need 5 cakes so multiply by 5

38.5g:5

4 0

3 years ago

Read 2 more answers

I am a square number. The sum of my digits is 7. what square might i be?

slamgirl [31]

Thee answer is 25. 25 is a square number as it is 5 times 5. The sum of the digits 2+5 is 7.

6 0

3 years ago

A sample of 5 buttons is randomly selected and the following diameters are measured in inches. Give a point estimate for the pop

Helen [10]

Answer:

$s^2 = \frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}$

But we need to calculate the mean with the following formula:

$\bar X = \frac{\sum_{i=1}^n X_I}{n}$

And replacing we got:

$\bar X = \frac{ 1.04+1.00+1.13+1.08+1.11}{5}= 1.072$

And for the sample variance we have:

$s^2 = \frac{(1.04-1.072)^2 +(1.00-1.072)^2 +(1.13-1.072)^2 +(1.08-1.072)^2 +(1.11-1.072)^2}{5-1}= 0.00277\ approx 0.003$

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance $\sigma^2$

$E(s^2) = \sigma^2$

Step-by-step explanation:

For this case we have the following data:

1.04,1.00,1.13,1.08,1.11

And in order to estimate the population variance we can use the sample variance formula:

$s^2 = \frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}$

But we need to calculate the mean with the following formula:

$\bar X = \frac{\sum_{i=1}^n X_I}{n}$

And replacing we got:

$\bar X = \frac{ 1.04+1.00+1.13+1.08+1.11}{5}= 1.072$

And for the sample variance we have:

$s^2 = \frac{(1.04-1.072)^2 +(1.00-1.072)^2 +(1.13-1.072)^2 +(1.08-1.072)^2 +(1.11-1.072)^2}{5-1}= 0.00277\ approx 0.003$

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance $\sigma^2$

$E(s^2) = \sigma^2$

3 0

3 years ago

Suppose the round-trip airfare between Philadelphia and Los Angeles a month before the departure date follows the normal probabi

QveST [7]

Answer:

52.74% probability that a randomly selected airfare between these two cities will be between $325 and $425

Step-by-step explanation:

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.

In this question, we have that:

$\mu = 387.20, \sigma = 68.50$