- #1
princejan7
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Homework Statement
http://postimg.org/image/bleosmrep/
Homework Equations
The Attempt at a Solution
can someone explain the last line of the solution; where did 1 - 6.25/10^2 come from?
princejan7 said:Homework Statement
http://postimg.org/image/bleosmrep/
Homework Equations
The Attempt at a Solution
can someone explain the last line of the solution; where did 1 - 6.25/10^2 come from?
Ray Vickson said:You are supposed to show your work (PF rules). So, first you need to tell us what you think the method is.
They're applying a standard inequality. What inequalities do you know which involve the mean and variance?princejan7 said:I'm not really sure what they're doing at all
I want to know why they reduced the original problem to P((X-u)<10)
A probability distribution is a mathematical function that describes the likelihood of different outcomes occurring in an experiment or event. It shows the possible values that a random variable can take and the probability of each of those values.
There are many types of probability distributions, but some of the most commonly used ones include the normal distribution, binomial distribution, Poisson distribution, and exponential distribution. Each distribution is used to model different types of data and situations.
A probability distribution is a graphical representation of the probability of different outcomes, while a probability density function (PDF) is a mathematical function that describes the probability of a continuous random variable falling within a certain range of values. In other words, a PDF is the mathematical expression of a probability distribution.
The mean of a probability distribution, also known as the expected value, is calculated by multiplying each possible value of the random variable by its corresponding probability and then summing all these values. It represents the center of the distribution and is denoted by the symbol µ.
Yes, probability distributions can be used to make predictions about the likelihood of certain events or outcomes occurring in the future. By understanding the characteristics of a specific distribution, such as its mean and standard deviation, we can make educated guesses about what may happen in the future based on past data.