we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.
The distribution for a variable is the set of value that the variable can take and the probabilities associated with those value.
mean deviation is minimum
i dont even no
Parametric statistics is a branch of statistics that assumes data come from a type of probability distribution and makes inferences about the parameters of the distribution. See related link.
Why we prefer Normal Distribution over the other distributions in Statistics
example of symmetrical distribution
Sampling distribution in statistics works by providing the probability distribution of a statistic based on a random sample. An example of this is figuring out the probability of running out of water on a camping trip.
we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.
Not necessarily. Inferential statistics are statistics which are used in making inferences about some distribution. The only requirement is that they are based only on the set of observed values.
It is probably the most widely used distribution in statistics. In addition, a lot of information exists on this distribution.
The distribution for a variable is the set of value that the variable can take and the probabilities associated with those value.
mean deviation is minimum
i dont even no
The Student's T- Distribution is a type of probability distribution that is theoretical and resembles a normal distribution. The Student T- Distribution differs from the normal distribution by its degrees of freedom.
Parametric statistics is a branch of statistics that assumes data come from a type of probability distribution and makes inferences about the parameters of the distribution. See related link.
Exponential distribution is a function of probability theory and statistics. This kind of distribution deals with continuous probability distributions and is part of the continuous analogue of the geometric distribution in math.