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).
Probability is the chance of some outcome while actuality is the realistic chance and actual outcome of an event.
the normal distribution is a bell shape and expeonential is rectangular
Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.
No, a distribution can have infinitely many moments: the first is the mean, the second variance. Then there are skewness (3), kurtosis (4), hyperskewness (5), hyperflatness (6) and so on.If mk represents the kth moment, thenmk = E[(X - m1)k] where E is the expected value.It is, therefore, perfectly possible for m1 and m2 to be the same but for the distribution to differ at the higher moments.
it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers
The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.
Probability/ Statistics
The standard normal distribution has a mean of 0 and a standard deviation of 1.
A continuous variable is one that can assume different values between each point. Put as an example (e.g when looking at height) one can assume a height of 178, 178.1, 178.2. . . 178.9. Thus continuous variables can be used when looking at time or length for example. Continuous variables will differ from discrete variables which assume a fixed value for example number of times you take a shower, how many cars you have or how many kids in a family. Values can not be specified as decimals (e.g. you can not have 1.2 cars or 2.7 kids in a family).
A continuous variable is one that can assume different values between each point. Put as an example (e.g when looking at height) one can assume a height of 178, 178.1, 178.2. . . 178.9. Thus continuous variables can be used when looking at time or length for example. Continuous variables will differ from discrete variables which assume a fixed value for example number of times you take a shower, how many cars you have or how many kids in a family. Values can not be specified as decimals (e.g. you can not have 1.2 cars or 2.7 kids in a family).
Probability is the chance of some outcome while actuality is the realistic chance and actual outcome of an event.
the normal distribution is a bell shape and expeonential is rectangular
Yes.
distribution of wealth
Single gene traits are either one type or another,for example everyone is either (ABO System) group A,B AB or O with no intermediates - this shows discontinuous variation. In polgyenic traits, continuous variation is shown and there is a range with no discrete categories - height
Selective distribution occurs when manufacturers distribute products through a limited, select number of wholesalers and retailers. Under exclusive distribution, only a single wholesaler or retailer is allowed to sell the product
France did not develop an institution that could limit the power of the king.