Cumulative Frequency Distribution
Cumulative Frequency Distribution - 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 m..
Discrete probability distribution
A discrete random variable assumes each of its values with a certain probability. Let X be a discrete random variable which takes values x 1 , x 2 , x 3 ,x n where p i = P{X = x i } Then X : x 1 x 2 x 3 x n P(X) : p 1 p 2 p 3 p n is called the probability distribution of x, If i..
A discrete random variable assumes each of its values with a certain probability. Let X be a discrete random variable which takes values x 1 , x 2 , x 3 ,x n where p i = P{X = x i } Then X : x 1 x 2 x 3 x n P(X) : p 1 p 2 p 3 p n is called the probability distribution of x, If i..Random Variables and Probability Distributions
Let S be a sample space associated with a given random experiment. A real valued function X which assigns to each w i S, a unique real number, X( w i ) = x i is called a random variable . Two types of random variables are 1. Continuous random variable, 2. discrete random varia..
Random Variables and Probability Distributions
It 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 1 0 x is called a random variable, which can assume the valu..
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 1 0 x is called a random variable, which can assume the v..
Bayes Theorem, Binomial and Poisson Distributions
Introduction - Suppose the two events are not independent, that is the occurrence of one depends on the occurrence of other, then how do we compute This can be explained by conditional probability. Baye's theorem is named after the British mathematician Thomas Bayes who published it in a research p..
Introduction - Suppose the two events are not independent, that is the occurrence of one depends on the occurrence of other, then how do we compute This can be explained by conditional probability. Baye's theorem is named after the British mathematician Thomas Bayes who published it in a research p..Statistics: Graphical Representation
The scientific methods of collection of data, its classification and application to commerce and everyday life is called statistics. A list of some important terms as follows: (i) ungrouped data (ii) tabulation of data (iii) range (iv) frequency (v) frequency distribution ..
Statistics XI Summary
Summary - The mean deviation (M.D) of a statistical data is defined as the arithmetic mean of the numerical values of the deviations of the items from some average. For an individual series, For a frequency distribution, If M.D is calculated about mean, then it is written as M.D (x)...
Summary - The mean deviation (M.D) of a statistical data is defined as the arithmetic mean of the numerical values of the deviations of the items from some average. For an individual series, For a frequency distribution, If M.D is calculated about mean, then it is written as M.D (x)...Example:
If the variance of the Poisson distribution is 2, find the probabilities for r = 1, 2, 3, 4 and 5 from the recurrence relation of the Poisson distribution..
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