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sweet [91]
2 years ago
9

What transformation was not done to the linear parent function, f(x) = x, to

Mathematics
1 answer:
Butoxors [25]2 years ago
7 0

Answer:

C.

Step-by-step explanation:

The function shifted <em>left</em> five units instead of <em>right</em> five units.

There's no vertical compression in the equation provided, but that's probably just a typo since there's a random bracket that I assume was supposed to be a fraction.

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In a business, if A can earn $7500 in 2.5 years, find the unit rate of his earning per month
andrew11 [14]

2.5 years = 30 months

7500$ in 30 months

x$ in 1 month

___________________

x = (7500*1)/30 = 250

The answer is 250$/month.

5 0
3 years ago
Read 2 more answers
My product is 30. The differencd of the two factors is 1. The zum of the two factors is 11. What numbers am i
timurjin [86]
A * b = 30
a - b = 1
a + b = 11

take ur last 2 equations, and add them
a - b = 1
a + b = 11
--------------add
2a = 12
a = 12/2
a = 6

now its just a matter of subbing
a + b = 11
6 + b = 11
b = 11 - 6
b = 5

so a = 6 and b = 5...whose product is 30, whose difference is 1, and whose sum is 11.
5 0
3 years ago
I travelled at 60km/h and took 2 hours for a certain journey. How long would it have taken me if I had travelled at 50km/h?​
Marina86 [1]

Answer:

2 hours and 24 minutes

Step-by-step explanation:

2 hours at 60 km/h means you have travelled 2*60=120 km

120 km at 50 km/h takes 120/50 = 2.4 hours

2.4 hours is 2 hours and 0.4*60 = 24 minutes.

7 0
3 years ago
Life Expectancies In a study of the life expectancy of people in a certain geographic region, the mean age at death was years an
Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}, in which \mu is the mean life expectancy, \sigma is the standard deviation and n is the size of the sample.

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 establishes 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.

We have:

Mean \mu, standard deviation \sigma.

Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

Find the probability that the mean life expectancy will be less than years.

The probability that the mean life expectancy of the sample is less than X years is the p-value of Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}, in which \mu is the mean life expectancy, \sigma is the standard deviation and n is the size of the sample.

8 0
2 years ago
I need help on this and if you the first person to answer this correctly then I would mark you BRANILIST​​​
lesantik [10]

Answer:

60

Step-by-step explanation:

8 0
3 years ago
Read 2 more answers
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