Can someone help me with Eurkea Math page 97 module 1? (Seventh grade)

Mathematics

1 answer:

Sauron [17]3 years ago

8 0

You want to make a skale. The scale would be 1/12 = in measured/x cross multiply and solve the equation.

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A store owner buys a case of 144 pens for $28.80. He sells the pens for $0.40 each. The owner claims that they marked the pens u

stellarik [79]

Answer: $0.3

Step-by-step explanation:

Given

The owner buys 144 pens for $28.80 i.e. each pen costs

$\dfrac{28.80}{144}=\$0.2$

owner sells the pen at $0.4 i.e. price marked up by

$\Rightarrow \dfrac{0.4-0.2}{0.2}\times 100=100\%$

So, the claim of the owner is incorrect

The actual increase in the price to get 50% markup

$\Rightarrow 0.2\times (1+0.5)=\$0.3$

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3 years ago

The average Act score follows a normal distribution, with a mean of 21.1 and a standard deviation of 5.1. What is the probabilit

ohaa [14]

Answer:

0.43% probability that the mean IQ score of 50 randomly selected people will be more than 23

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