Ella has 50 stacks of ten pennies in each stack described how to find how many pennies ella has in all

Mathematics

2 answers:

musickatia [10]2 years ago

8 0

You have to do 10 x 50 bc she 50 stacks of 10 pennies

mario62 [17]2 years ago

3 0

First, find the amount of pennies in each stack, which is ten as the problem says. Next, multiply the number of stacks by the number of pennies in each stack (50 x 10). That will be your answer. Hope this helps!

You might be interested in

QUESTION THREE (30 MARKS) 3.1 The mass of a standard loaf of white bread is, by law meant to be 700g with a population standard

kiruha [24]

Using the normal distribution and the central limit theorem, it is found that there is a 0.0284 = 2.84% probability of finding a sample mean mass of 695g or below.

----------------------------------

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

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

----------------------------------

Mean of 700g means that $\mu = 700$
Standard deviation of 21g means that $\sigma = 21$
Sample of 64, thus $n = 64$
<u>For the sampling distribution of the sample mean</u>, the standard deviation is of $s = \frac{21}{\sqrt{64}} = \frac{21}{8} = 2.625$