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Svet_ta [14]
3 years ago
7

A discount store takes 50% off of the retail price of a desk. For the store's holiday sale, it takes an additional 20% off of al

l furniture. The desk's retail price was $320. How much is the desk on sale for during the holiday sale? 
Mathematics
2 answers:
horrorfan [7]3 years ago
6 0

store gives 50% and additional 20 % offer on furniture

50 % is for desk and additional 20% is for furniture we know dest belongs to furniture category.

so total discount is 70 %

we know that cost price of desk $320 dollar

so after the discount value cost will be =70/100*320=0.7*320=224

we will have discount of 224 from 320

so sale price will be =320 -224=$96.

Serhud [2]3 years ago
3 0

We are given the retail price of desk as $320. The store takes 50% off of the retail price of desk, then its price would become half of the original.

So its new price would be $160.

Now it says that it takes an additional 20% off of all furniture on store's holiday sale. So we need to cut off 20% from new price $160.

Holiday discount = 20% of $160 = 0.2 × 160 = 32.

Final selling price would be = $160 - $32 = $128.

So $128 is the final answer.

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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.

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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 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}}.

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