Which rate is the lowest price? $5.60 for 8 $4.80 for 6 $4.50 for 5 $0.75 each

1 answer:

3 0

You can calculate percentages by first finding what 10% of a value is and then what 5 or 1% is. From there you can multiply to find multiples and then add to get the required percentage. The example below shows this.

What is 35% of $40?Step 1What is 10% of $40?10% of $40 = $40 ÷ 10 = $410% is a relatively easy percentage and can be found by dividing by 10.Step 23 x $4 = $1230% of $40 = $1230% is 3 times ( 3 x) 10% so we multiply what 10% of $40 is by 3Step 3What is 5% of $40?5% of $40 = $4 ÷ 2 = $25% is half of what 10% is so divide what 10% is by 2 .Step 4What is 35% of $40?$12 + $2 = $14Add what

You might be interested in

If Sarah has 50 Nickles and 20 dimes and Bill has 230 pennies and 5 quarters. Who has the more amount of money?

ser-zykov [4K]

Hi,

Your Question states: If Sarah has 50 Nickles and 20 dimes and Bill has 230 pennies and 5 quarters. Who has the more amount of money?

Answer: Sarah

Explanation: Sarah amount is $2.50, because the amount of nickels is 5 cents and if you multiply 5 times 50 you answer becomes $2.50. 20 dimes and every dime is 10 multiples up to $2.00. 230 is $2.30, and 5 quarters each being 25 cents is $1.25 so your answer is Sarah with 50 nickels.

I Hope I Helped!

~KingJupiter

8 0

4 years ago

Read 2 more answers

For reviewing purposes

sergeinik [125]

Answer:

(25-16)/9=

=9/9=1 because 5^2 is 25 and 3^2 is 9 (5x5)/(3x3)

5 0

3 years ago

Rockwell hardness of pins of a certain type is known to have a mean value of 50 and a standard deviation of 1.8. (Round your ans

Alenkinab [10]

Answer:

a) 0.011 = 1.1% probability that the sample mean hardness for a random sample of 17 pins is at least 51

b) 0.0001 = 0.1% probability that the sample mean hardness for a random sample of 45 pins is at least 51

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 normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.

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 $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .