Continuous probability problem

In summary, the conversation discusses the probability density function for the length of satisfactory service provided by a certain model of laptop computer and how to find the probabilities for different time intervals. The solution involves evaluating an integral and the probabilities are determined to be approximately 0.4262, 0.1475, and 0.2231 for intervals of 2.5 years, 4 to 6 years, and at least 6.75 years, respectively.
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toothpaste666
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Homework Statement



The length of satisfactory service (years) provided by a certain model of laptop computer is a random variable having the probability density
f(x) = (1/4.5)e^(-x/4.5) for x > 0
and 0 for x <= 0

find the probabilities that one of these laptops will provide satisfactory service for
a) at most 2.5 years
b) anywhere from 4 to 6 years
c) at least 6.75 years

The Attempt at a Solution


first we evaluate the integral

∫(1/4.5)e^(-x/4.5)dx = (1/4.5) ∫ e^(-x/4.5)dx = (1/4.5)(-4.5)e^(-x/4.5) = -e^(-x/4.5)

part a) evaluate from 0 to 2.5

-e^(-2.5/4.5) - (-e^0) = 1 - e^(-2.5/4.5) = .4262

b) evaluate from 4 to 6
-(e^(-6/4.5) - e^(-4/4.5)) = .1475

c) from 6.75 to ∞
-(e^(-∞) - e^(-6.75/4.5)) = -(0 - .2231) = .2231

is my reasoning correct?
 
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  • #2
Yes. It is correct.
 
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Likes toothpaste666
  • #3
thank you
 

1. What is a continuous probability problem?

A continuous probability problem is a type of statistical problem that involves calculating the probability of an outcome within a continuous range of values. This is in contrast to discrete probability problems, which involve calculating the probability of specific events or outcomes.

2. How is continuous probability different from discrete probability?

The main difference between continuous and discrete probability is that continuous probability deals with variables that can take on any value within a range, while discrete probability deals with variables that can only take on specific, distinct values. Continuous probability also requires the use of calculus and integration to calculate probabilities, while discrete probability uses simpler methods such as counting and permutations.

3. What are some real-world examples of continuous probability problems?

Continuous probability problems can be found in various fields such as finance, physics, and biology. For example, calculating the probability of a stock price falling within a certain range, determining the probability of a particle's position at a specific time, or estimating the probability of a person's height falling within a certain range are all examples of continuous probability problems.

4. How do you solve a continuous probability problem?

To solve a continuous probability problem, you first need to define the range of values and the probability distribution of the variable in question. Then, you can use integration to calculate the area under the curve of the probability distribution within the given range. This area represents the probability of the variable falling within that range.

5. What are some applications of continuous probability?

Continuous probability has many practical applications, such as risk analysis in finance, modeling natural phenomena in physics, and predicting outcomes in biology. It is also used in decision-making processes, such as determining the optimal production level in manufacturing or the ideal pricing strategy for a product.

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