The answer is 0.1586
.820=82.0%
Approx 0.0027
Pr(Z > -2) = 97.725%
There is not enough information about the the distribution of the number of people known by each individual - nor the averages. It is therefore no possible to give an answer any more precise than "the probability will be infinitesimally small".
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
.820=82.0%
To find the probability of a randomly selected woman having a height within a specific range, we can use the normal distribution with the given mean (μ = 63.6 inches) and standard deviation (σ = 2.1 inches). For instance, if we want to find the probability that a randomly selected woman is shorter than 65 inches, we would calculate the z-score using the formula ( z = \frac{(X - \mu)}{\sigma} ), where ( X ) is the height in question. After calculating the z-score, we would consult the standard normal distribution table or use a calculator to find the corresponding probability. If you have a specific height range in mind, please specify for a more detailed calculation.
Approx 0.0027
Pr(Z > -2) = 97.725%
There is not enough information about the the distribution of the number of people known by each individual - nor the averages. It is therefore no possible to give an answer any more precise than "the probability will be infinitesimally small".
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.
Assuming the uniform continuous distribution, the answer is 29/49. With the uniform discrete distribution, the answer is 29/50.
An example of random dispersion would be the distribution of seeds dispersed by the wind in a forest. The seeds are scattered randomly based on wind direction and speed, resulting in a random pattern of distribution across the forest floor.
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
To find the probability of a randomly selected applicant receiving a credit rating above a certain value, you would first need to determine that value. For example, if you want to find the probability of an applicant having a rating above 250, you would calculate the z-score using the formula ( z = \frac{(X - \mu)}{\sigma} ), where ( X ) is the rating, ( \mu ) is the mean (200), and ( \sigma ) is the standard deviation (50). After calculating the z-score, you can use the standard normal distribution table or a calculator to find the corresponding probability.
hypergeometric distribution f(k;N,n,m) = f(1;51,3,1) or binominal distribution f(k;n,p) = f(1;1,3/51) would result in same probability
Non probability sampling is where the samples are not selected randomly.