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What is the probability the random variable will assume a value between 40 and 60?
It depends on what the random variable is, what its domain is, what its probability distribution function is. The probability that a randomly selected random variable has a value between 40 and 60 is probably quite close to zero.
Why does a researcher want to go from a normal distribution to a standard normal distribution?
A researcher wants to go from a normal distribution to a standard normal distribution because the latter allows him/her to make the correspondence between the area and the probability. Though events in the real world rarely follow a standard normal distribution, z-scores are convenient calculations of area that can be used with any/all normal distributions. Meaning: once a researcher has translated raw data into a standard normal distribution (z-score), he/she can then find its associated probability.
How do you find the probability between two values given the population mean and standard deviation?
The answer depends on the distribution of the random variable. For some variables it is easy to calculate the cumulative distribution, F(x).Then, the probability between the values p and q is F(q) - F(p). WARNING: This might need minor modification if the the distribution is discrete.The normal distribution is one which, in general, cannot be evaluated analytically. However, you can convert p and q to the x=corresponding z-score. If m is the mean and s the standard deviations, then z1 = (p - m)/s and z2 = (q - m)/s. The cumulative probability function for Z is tabulated (widely available online) and the probability between p and q is F(z2) - F(z1).Note, however, that sometimes the tabulated values are (Prob - 0.5), or are 1 - Prob(z) so read notes to the table.
What happens to the probability of observing a t-random variable between -2 and 2 as you increase the degrees of freedom?
The probability increases.The probability increases.The probability increases.The probability increases.
What is the difference between dependent and independent events in terms of probability?
What is the difference between dependant and independent events in terms of probability
What the difference between a probability distribution and a probability function?
None. The full name is the Probability Distribution Function (pdf).
What the difference and relationship between a probability distribution and a probability function?
They are the same. The full name is the Probability Distribution Function (pdf).
Distinguish between binomial distribution and normal distribution?
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
What is an important difference between the uniform and normal probability distributions?
The uniform distribution is limited to a finite domain, the normal is not.
What is the difference between probability distribution and probability density function?
A probability density function assigns a probability value for each point in the domain of the random variable. The probability distribution assigns the same probability to subsets of that domain.
Similarity between the uniform and normal probability distributions?
They are continuous, symmetric.
How does a discrete probability distribution differ from a continuous probability distribution?
A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).
Difference between a random variable and a probability distribution is?
A random variable is a variable that can take different values according to a process, at least part of which is random.For a discrete random variable (RV), a probability distribution is a function that assigns, to each value of the RV, the probability that the RV takes that value.The probability of a continuous RV taking any specificvalue is always 0 and the distribution is a density function such that the probability of the RV taking a value between x and y is the area under the distribution function between x and y.
Relationship between Exponential and Poisson Distributions?
Poisson distribution shows the probability of a given number of events occurring in a fixed interval of time. Example; if average of 5 cars are passing through in 1 minute. probability of 4 cars passing can be calculated by using Poisson distribution. Exponential distribution shows the probability of waiting times between occurrences of events. If we use the same example; probability of a car coming in next 40 seconds can be calculated by using exponential distribution. -Poisson : probability of x times occurrence -Exponential : probability of waiting times between events.
What is the difference between a probability density curve and cummulative distribution function?
what is density curve
The probability density function for a uniform distribution ranging between 2 and 6 is?
4
The probability density function has what value in the interval between 20 and 28?
I think you left off some important information. Perhaps you can supply this information, to obtain assistance. To calculate the probability or the chance of occurrence between two values, we calculate: Pr{a < X < b} = F(b) - F(a) where F(x) = cumulative probability distribution. The distribution requires certain known parameters. In the case of the Normal distribution, the mean and standard deviation are parameters. In your particular case, a = 20 and b = 28.
