How do you do this I am so confused please help me

A printing company orders paper from two different suppliers. Supplier X charges $25 per case. Supplier Y charges $20 per case.

Lana71 [14]

Let x = the number of cases from Supplier X and
y = the number of cases from Supplier Y

From the statement "The company needs to order at least 45 cases per day"
x + y ≥ 45
From "The company can order no more than 30 cases from Supplier X"
x ≤ 30
From the statement "the company needs no more than 2 times as many cases from Supplier Y as from Supplier X".
y ≤ 2x

4 0

4 years ago

What does the transformation f(x)↦f(-x) do to the graph of f(x)?

Vlad1618 [11]

The function will simply get reflected about the y-axis.
Let's approach this through what we know. Since we know that the x values are mirrored, we know that the points in Quadrant I and IV will be reflected over to the negative side, Quadrants II and III, because they simply change in signs.

However, we also know that the function y-values do not change. This is because whatever the x values are don't change the range and y-values of an even function.

To be more specific, if we have an even function, we are most likely dealing with quadratics or variants/transformations of the quadratic function.

If we were to have 2, and -2, and we wanted to plug them into the equation:
$y = x^{2} + C$ , the signs do not change the y-values of the function.
Hence, we know that it ONLY gets reflected across the y-axis.

6 0

3 years ago

A sample of 125 pieces of yarn had mean breaking strength 6.1 N and standard deviation 0.7 N. A new batch of yarn was made, usin

AlexFokin [52]

Answer:

The 90% confidence interval for the difference in mean breaking strength between the two types of yarn is (0.08N, 0.52N).

Step-by-step explanation:

Before building the confidence interval, we need to understand the central limit theorem and subtraction of normal variables.

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

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

Subtraction of normal variables:

When we subtract two normal variables, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

A sample of 125 pieces of yarn had mean breaking strength 6.1 N and standard deviation 0.7 N.

This means that $\mu_1 = 6.1, s_1 = \frac{0.7}{\sqrt{125}} = 0.0626$