2 1/4 cups = how many pints

The total cost, in dollars, to order x units of a certain product is modeled by C(x)=5x²+320 . According to the model, for what

lora16 [44]

Answer:

The minimum cost per unit is obtained for an order of 8 units.

Step-by-step explanation:

Since the total cost is modeled by;

C(x)=5x²+320

Then;

1 unit costs; C(x)=5(1)²+320 = 325

cost per unit 325/1 = 325

8 units costs; C(x)=5(8)²+320 = 640

cost per unit = 640/8 = 80

80 units costs; C(x)=5(80)²+320 = 32320

Cost per unit = 32320/80 = 404

The minimum cost per unit is obtained for an order of 8 units.

7 0

2 years ago

where would an imaginary line need to be drawn to reflect across an axis of symmetry so that a regular pentagon can carry onto i

irina [24]

Answer:

An imaginary line would need to be drawn at any angle to the center of the side opposite the angle to reflect across an axis of symmetry so that a regular pentagon can carry onto itself. Hope this answer helps.

5 0

2 years ago

ASAP NEED HELP ON MY MATH RETAKE I NEED HELP PLZZZ IM BEGGING YALL

Sindrei [870]

Answer:

B) There tends to be a linear association between variables

c) the data includes one or more outliers

8 0

3 years ago

The mean height of women in a country (ages 20-29) is 64 4 inches A random sample of 50 women in this age group is selected What

Simora [160]

Answer:

0.0721 = 7.21% probability that the mean height for the sample is greater than 65 inches.

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 $s = \frac{\sigma}{\sqrt{n}}$ .