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3 years ago

You have $6.17. you buy 7 items that cost $0.76 each. how much money do you have left

Mathematics

2 answers:

Shkiper50 [21]3 years ago

6 0

Answer:

$0.85

Step-by-step explanation:

if you multiply 7x0.76=5.32

and then subtract the 6.17-5.32=$.85

Klio2033 [76]3 years ago

5 0

Answer:

.85

Step-by-step explanation:

Multiply .76x7 then subtract 5.32 from 6.17 and you get 0.85.

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There are only blue cubes,yellow cubes and green cubes in a bag.There are twice as many blue cubes as yellow cubes and four time

USPshnik [31]

Hey there :)

Let us translate the sentence into mathematics step by step:
There are twice as many as blue cubes as yellow cubes
2 x yellow = 2 cubes = blue
1 cube = yellow

There are four times as many as green cubes as blue cubes
4 x 2 ( blue cubes ) = 8 cubes = green

Total cubes = yellow + blue + green
= 1 + 2 + 8
= 11

Hannah takes random cube
Probability that Hannah takes yellow cube:
P = number of Yellow cubes ÷ Total number of cubes
P = $\frac{1}{11}$

4 0

3 years ago

A company makes windows for use in homes and commercial buildings. The standards for glass thickness call for the glass to avera

guajiro [1.7K]

The question is incomplete. The complete question follows.

A company makes windows for use in homes and commercial builidings. The standards for glass thickness call for the glass to average 0.325 inch with a standard deviation equal to 0.065 inch. Suppose a random sample of n=44 windows yield a sample mean of 0.337 inch. Complete parts a and b.

a. What is the probability of x ≥ 0.337 if the windows meet the standards?

b. Based on your answer to part a, what would you conclude about the population of windows? Is it meeting the standards? (A result is unusual if it has a probability less than 0.05)

Answer and Step-by-step explanation: To answer this question, use <u><em>Central Limit Theorem</em></u>: it states regardless of the original population distribution, if the sample size is large enough, the sample mean distribution will approach a normal distribution.

The calculations for the CLT is given by normalizing the distribution, i.e.:

$z=\frac{x-\mu}{\sigma/\sqrt{n} }$

where

z is z-score

x is the sample mean

μ is population mean

σ is standard deviation of the population

n is the number of individuals in the sample

Calculating z-score for the window maker company:

$z=\frac{0.337-0.325}{0.065/\sqrt{44} }$

$z=\frac{0.012}{0.0098}$

z = 1.22

Using the z-score table, we found the probability:

P = 0.8888

As it is a "more than situation":

P(x≥0.337) = 1 - 0.8888

P(x≥0.337) = 0.1112 or 11.12%

a. Probability of x≥0.337 if the windows meet the standards is 11.12%.

b. Comparing results, probability of x≥0.337 is bigger than 0.05:

0.1112 > 0.05

So, we can conclude that the random sample of n=44 is meeting the standards estipulated.

7 0

2 years ago

Payne saves $2,000 at a yearly simple interest rate of 2%. He earns $280 in interest. How many years did he save his money?

Flauer [41]

The answer if 7 years, if you multiply 2,000 by .02 it equals 40. so you divide 280 by 40 and get 7

6 0

3 years ago

Tyler ate x fruit snacks, and Han ate 3/4 less that. write an expression for the number of fruit snacks Han ate

Alika [10]

x = ×-3/4

because you hace the variable x and you do not know the number of fruit snacks he ate and you need to have the same variables to properly find the answer.

3 0

3 years ago

A manufacturer of computer printers purchases plastic ink cartridges from a vendor. When a large shipment is received, a random

g100num [7]

Answer:

97.4% probability

Step-by-step explanation:

Since there is only two possible outcome of inspecting the catridge : either defective or not, we can solve the problem using the binomial probability distribution (approximated to normal).

To approximate the binomial probability to normal, we find the expected value and the standard deviation of the probability of exactly x sucesses on n repeated trials with p probability

Expected values E(X) = np

Standard deviation √V(X) = √np(1-p)

using the z-score formula (X - μ)/σ, we can solve normally distributed problem.

Where μ is the mean and σ is the standard deviation. The Z-score is is the measure of how much a sample is from the mean. The p-value associated with this z-score which is the probability that the value of the measure is smaller than X can be checked on the z-score table.

FOR THIS QUESTION,

a random sample of 200 cartridges is selected

n = 200

Therefore If there are more than 0.02 × 200 = 4 defective, the sample will be returned.

To determine the approximate probability that a shipment will be returned if the true proportion of defective cartridges in the shipment is 0.05

μ = E(X)

= 0.05 × 200 = 10

σ = √V(X) = √np(1-p)

= √200 × 0.05 × 0.95

= 3.08

This probability is 1 subtracted by the pvalue of Z when X =4

Z = (X - μ)/σ

Z= (4 - 10)/3.08

Z = -1.95

Z = -1.95 has a P-value of 0.026 (on the z-score table)

This means that there is a 1 - 0.026 = 0.974

= 97.4% probability that a shipment will be returned if the true proportion of defective cartridges in the shipment is 0.05.

6 0

3 years ago