Ask question

Ask question

All categories

elena-14-01-66 [18.8K]

2 years ago

10

What is the effect on the graph of the function f(x) = 2x when f(x) is replaced with f(x − 3 5 )? A) translate vertically 3 5 un

its up B) translate vertically 3 5 units down C) translate horizontally 3 5 units left D) translate horizontally 3 5 units right

1 answer:

Arte-miy333 [17]2 years ago

3 0

Answer:

D.

Step-by-step explanation:

Translates horizontally 3.5 units right.

You might be interested in

Rewrite the decimal as the front as a fraction in simplest form 0.27

torisob [31]

So .27 means .27/1 or 2.7/10 or 27/100 or 270/1000 and so on

6 0

2 years ago

Read 2 more answers

Need Help with this question

Fantom [35]

82
The sum of the three angles is 180. One is given and the other we can figure out because it forms a straight line (180) with the angle to the left outside. The outside angle is 117, so 180-117 is 63.
So then add up the 3 angles in the triangle
63+35+y=180
y= 82

3 0

2 years ago

The 1985 Mexico City earthquake measured a magnitude 8.0 on the Richter scale. The Richter scale uses the function M (I) = log (

Travka [436]

Answer:

The correct option is C: I = 10⁸I₀.

Step-by-step explanation:

The function of the Richter scale is:

$M_{(I)} = log(\frac{I}{I_{0}})$

Since the magnitude of the earthquake is 8.0, the relation between the intensity, I, with the intensity of the threshold quake, Io, is:

$8.0 = log(\frac{I}{I_{0}})$

$10^{8} = \frac{I}{I_{0}}$

$I = 10^{8}I_{0}$

Therefore, the correct option is C: I = 10⁸I₀.

I hope it helps you!

7 0

3 years ago

The distribution of weekly salaries at a large company is right skewed with a mean of $1000 and a standard deviation of $350. Wh

Shtirlitz [24]

Answer:

68.76% probability that the sampling error made in estimating the mean weekly salary for all employees of the company by the mean of a random sample of weekly salaries of 50 employees will be at most $50

Step-by-step explanation:

To solve this question, we have 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 random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation, which is also called standard error $s = \frac{\sigma}{\sqrt{n}}$

In this problem, we have that:

$\mu = 1000, \sigma = 350, n = 50, s = \frac{350}{\sqrt{50}} = 49.5$

What is the probability that the sampling error made in estimating the mean weekly salary for all employees of the company by the mean of a random sample of weekly salaries of 50 employees will be at most $50

This is the pvalue of Z when X = 1000+50 = 1050 subtracted by the pvalue of Z when X = 1000-50 = 950. So

X = 1050

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

By the Central Limit Theorem

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

$Z = \frac{1050-1000}{49.5}$

$Z = 1.01$

$Z = 1.01$ has a pvalue of 0.8438

X = 950

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

$Z = \frac{950-1000}{49.5}$

$Z = -1.01$

$Z = -1.01$ has a pvalue of 0.1562

0.8438 - 0.1562 = 0.6876

68.76% probability that the sampling error made in estimating the mean weekly salary for all employees of the company by the mean of a random sample of weekly salaries of 50 employees will be at most $50

4 0

2 years ago

Five minus three fourths

Goryan [66]

5-3 5 3 20 3
__= _-_ = __-__=
4 1 4 4 4

17
___
4
I divide it the number to get the same denominator and do it on the top too.

8 0

3 years ago