Expected Value and Standard Deviation of A1 Computer's Rebate

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  • #1
geforce
26
0
A1 Computer has 15 tablets stocked, but four of them were actually defectives.
A client bought two tablets from A1 Computer. If both of them are good, things are fi ne.
If the client gets one defective machine, A1 Computer will replace it and give a $100 rebate
to the client. If the clients gets two defective machines, A1 Computer will replace both of
them and give a $1000 rebate to the client. What is the expected value and the standard
deviation of the company's rebate?

P(R) = 4/15 x 100 = 26.6%

Since there were 4 defective machines then 2 x 1000 = 2000 was given away to client(s)
so value = 2000
how would I find the standard deviation? I know the usual formula but where would i plug into it?
 
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  • #2
I think you are completely misunderstanding the problem.

You calculated P(R), the probability that a given computer is bad. Now What is the probability that, of 2 computers chosen at random from those 15
1) neither is bad.
2) one is bad.
3) both are bad.
 
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  • #3
geforce said:
A1 Computer has 15 tablets stocked, but four of them were actually defectives.
A client bought two tablets from A1 Computer. If both of them are good, things are fi ne.
If the client gets one defective machine, A1 Computer will replace it and give a $100 rebate
to the client. If the clients gets two defective machines, A1 Computer will replace both of
them and give a $1000 rebate to the client. What is the expected value and the standard
deviation of the company's rebate?

P(R) = 4/15 x 100 = 26.6%

Since there were 4 defective machines then 2 x 1000 = 2000 was given away to client(s)
so value = 2000
how would I find the standard deviation? I know the usual formula but where would i plug into it?

I don't understand. If you know the formula, what is preventing you from substituting in the appropriate numbers and doing the arithmetic? Or, are you saying that you don't know what numbers to plug in?

RGV
 

FAQ: Expected Value and Standard Deviation of A1 Computer's Rebate

1. What is the difference between statistics and probability?

Statistics is the study of data collection, organization, analysis, and interpretation. It involves using mathematical methods to analyze and draw conclusions from data. Probability, on the other hand, is the measure of the likelihood of an event occurring. It uses mathematical principles to predict the chances of certain outcomes.

2. What are the main types of probability?

The three main types of probability are classical, empirical, and subjective. Classical probability is based on a theoretical assumption that all outcomes have an equal chance of occurring. Empirical probability is based on observations and data collected from past events. Subjective probability is based on personal beliefs or opinions about the likelihood of an event occurring.

3. How is probability used in statistics?

Probability is used in statistics to make predictions and draw conclusions about a population based on a sample. It helps in determining the likelihood of different outcomes and can be used to assess risk and make informed decisions.

4. What is the difference between dependent and independent events in probability?

Independent events are events where the outcome of one event does not affect the outcome of another event. For example, flipping a coin twice, the outcome of the first flip does not affect the outcome of the second flip. Dependent events, on the other hand, are events where the outcome of one event does affect the outcome of another event. For example, drawing two cards from a deck without replacing the first card, the probability of drawing the second card will depend on the outcome of the first draw.

5. What is the central limit theorem and why is it important in statistics?

The central limit theorem states that as the sample size increases, the sample mean will approach the population mean, and the sampling distribution of the sample mean will become normally distributed. This theorem is important in statistics because it allows us to make inferences about a population based on a smaller sample. It also helps in understanding the behavior of sample means and allows for more accurate statistical analysis.

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