statistics and distributions

Probability: Interpreting probability, including long-run relative frequency interpretation 'Law of Large Numbers' concept Addition rule, multiplication rule, conditional probability, and independence Discrete random variables and their probability distributions, including bin..

Constructing and interpreting graphical displays of distributions of univariate data: Dotplot, stemplot, histogram, cumulative frequency plot Center and spread Clusters and gaps Outliners and other unusual features Shape Summarizing distributions of univari..

The number which tells us how many times a particular data appears is called the frequency. For example, 2 marks have been scored by five students which means marks 2 occurs five times. Therefore, the frequency of score 2 is five. Similarly, the frequency of marks 5 is three because three stu..

A trial, which has only two outcomes i.e., "a success" or "a failure", is called a Bernoulli trial . The probability distribution of the number of successes, so obtained is called the binomial distribution..

Poisson distribution is a limiting process of binomial distribution. Poisson distribution occurs when there are events which do not occur as outcomes of a definite number of outcomes. Poisson distribution is used under the following conditions: Number of tria..

A teacher gave a test to a class of 26 students. The maximum mark is 5. The marks obtained by the pupils are: Such data as above is called ungrouped (or raw) data. We may arrange the marks in ascending or descending order. The data so represented is called an array. The difference between the great..

If x is a discrete random variable assuming the values x 1 , x 2 , x 3 ,….,x n with probabilities p 1 , p 2 , p 3 ,…., p n respectively then (x 1 ,p 1 ), (x 2 , p 2 ),…(x n , p n ) defines a probability distribution of X. Mathematical Expectation of X or Mean of..

We shall now deduce the Poisson distribution from the binomial distribution by assuming that n and p 0 such that the product np always remains finite, say l . We shall now use a very important result of limits in Calcu..

Random Variable and Probability Distribution - If is often very important to allocate a numerical value to an outcome of a random experiment. For example consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome : HH HT TH TT No. of heads (x) : 2 1 ..

Cumulative frequency is obtained by adding the frequency of a class interval and the frequencies of the preceding intervals upto that class interval. This is explained by an example below. The following frequency distribution table gives the marks obtained by 40 students: Table (a) The fr..