A) Composite function that represents how many flowers Iris can expect to bloom over a certain number of weeks is f[s(w)] = 50w + 25.
B) The unit of measurement for the composite function is flowers.
C) Number of the flowers for 30 weeks will be 1525.
<h3>What is a composite function?</h3>
A function is said to be a composite function when a function is written in another function. The composite function that represents the number of flowers is f[s(w)] = 50w + 25. and the number of flowers for 30 weeks is 1525.
Part A: Write a composite function that represents how many flowers Iris can expect to bloom over a certain number of weeks.
From the given data we will find the function for the number of flowers with time.
f(s) = 2s + 25
We have s(w) = 25w
f[(s(w)]=2s(w) + 25
f[(s(w)] = 2 x ( 25w ) +25
f[s(w)] = 50w + 25.
Part B: What are the units of measurement for the composite function in Part A
The expression f[s(w)] = 50w + 25 will give the number of the flowers blooming over a number of the weeks so the unit of measurement will be flowers.
Part C: Evaluate the composite function in Part A for 30 weeks.
The expression f[s(w)] = 50w + 25 will be used to find the number of flowers blooming in 30 weeks put the value w = 30 to get the number of the flowers.
f[s(w)] = 50w + 25.
f[s(w)] = (50 x 30) + 25.
f[s(w)] = 1525 flowers.
Therefore the composite function is f[s(w)] = 50w + 25. unit will be flowers and the number of flowers in 30 weeks will be 1525.
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Answer: $55.33
Step-by-step explanation: In order to solve this promblem, add all the monthly gas bills and take that result and divide it by the numbe rof months, to get the anerage gas bill expense
Answer:
Person 2
Step-by-step explanation:
Person 1 has a rate of .45 in 3/4 hour, and Person 2 has a rate of .53 in 2/3 hour. 2/3 is less than 3/4 and 0.53 is bigger than 0.45.
Answer:
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 80 employees will be at most $75 is 0.9297.
Step-by-step explanation:
According to the Central Limit Theorem if we have a non-normal population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.
Then, the mean of the distribution of sample means is given by,
And the standard deviation of the distribution of sample means is given by,
The information provided is:
As <em>n</em> = 80 > 30, the central limit theorem can be used to approximate the sampling distribution of sample mean weekly salaries.
Let represent the sample mean weekly salaries.
The distribution of is:
Now we need to compute the probability of the sampling error made in estimating the mean weekly salary to be at most $75.
The sampling error is the the difference between the estimated value of the parameter and the actual value of the parameter, i.e. in this case the sampling error is, .
Compute the probability as follows:
Thus, 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 80 employees will be at most $75 is 0.9297.
Jason hit 11 homeruns.
Step-by-step explanation:
Homeruns hit by Nathan = 19
Let,
Homeruns hit by Nathan = x
Homerun hit by Jason = y
According to given statement;
x = 2y - 3 Eqn 1
We know that Nathan hit 19 homeruns, therefore, putting x=19 in Eqn 1
Dividing both sides by 2;
Jason hit 11 homeruns.
Keywords: linear equations, addition
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