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lora16 [44]
4 years ago
15

A salesman gets a commission of 2.4% on sales up to sh. 100,000. He gets an additional commission of 1.5% on sales above this. C

alculate the commission he gets on sales worth sh. 280,000
Mathematics
1 answer:
emmainna [20.7K]4 years ago
6 0

Answer:

Sh. 10,920

Step-by-step explanation:

Since the sales is above sh. 100,000,his commission is (2.4+1.5) 3.9%.

3.9% of 280,000= 10920.

Therefore, his commission is sh. 10,920

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What is the common ratio of the geometric sequence below?
Vadim26 [7]

Answer:

\textbf{Option C - $0.1$}\\

Step-by-step explanation:

\textup{A geometric series is given by}\\$ a, ar, ar^2, ar^3,. . . , ar^{n-1}, ar^n $ \\\textup{\textbf{Geometric progression or GP is a sequence of numbers in which the next number in the sequence is obtained by multiplying a number to the previous number in the sequence.}}\\

\textup{This number is constant through out the sequence and is denoted by $r$. it is given by $r = \frac{ar^n}{ar^{n-1}}$} \\

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$i.e., a = 70, ar = 7$\\

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Suppose data made available through a health system tracker showed health expenditures were $10,348 per person in the United Sta
nignag [31]

Answer:

a) 30.08% probability the sample mean will be within $100 of the population mean.

b) 0% probability the sample mean will be greater than $12,600

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the Central Limit Theorem.

Normal probability distribution

When the distribution is normal, we use 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}}.

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

In this question, we have that:

\mu = 10348, \sigma = 2500, n = 100, s = \frac{2500}{\sqrt{100}} = 250

a. What is the probability the sample mean will be within ±$100 of the population mean?

This is the pvalue of Z when X = 100 divided by s subtracted by the pvalue of Z when X = -100 divided by s. So

Z = \frac{100}{250} = 0.4

Z = -\frac{100}{250} = -0.4

Z = 0.4 has a pvalue of 0.6554, Z = -0.4 has a pvalue of 0.3556

0.6554 - 0.3546 = 0.3008

30.08% probability the sample mean will be within $100 of the population mean.

b. What is the probability the sample mean will be greater than $12,600?

This is 1 subtracted by the pvalue of Z when X = 12600. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{12600 - 10348}{250}

Z = 9

Z = 9 has a pvalue of 1.

1 - 1 = 0

0% probability the sample mean will be greater than $12,600

5 0
3 years ago
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