Get Professional Statistics Assignment Help in Continuous Probability assignment. Tutorchrome statistics assignment tutors offer 24x7 Continuous Probability Assignment Writing Help to university students across the USA, Canada, UK, Australia and UAE countries.

CONTINUOUS PROBABILITY DISTRIBUTIONS

Continuous data are data that can take on an infinite number of values between any two points and the examples are the weights and lengths, as well as time, are all usually considered as continuous data. If a random variable is a continuous variable, then its probability distribution can be defined as the continuous probability distribution.

In order to describe continuous data using a probability density function, a smooth curve is used for which area under the curve between two points on the horizontal axis signifies probability of an observation. The observations usually fall between these two points.

A continuous probability distribution differs from a discrete probability distribution in several ways when the probability that a continuous random variable will assume a particular value that is zero. So continuous probability distribution cannot be expressed in tabular form and instead, an equation or formula is used to describe a continuous probability distribution.

 

Continuous Probability Assignment Help

The equation used to describe a continuous probability distribution is called a probability density function that is pdf where all the probability density functions satisfy the following conditions such as the random variable Y is a function of X; that is, y = f(x). The y has a value which is greater than or equal to zero for all values of x and so the total area under the curve of the function is equal to one.

The charts below show two continuous probability distributions and the chart on the left shows a probability density function described by the equation y = 1 over the range of 0 to 1 and y = 0 elsewhere. The chart on the right depicts a probability density function described by the equation y = 1 - 0.5x over the range of 0 to 2 and y = 0 elsewhere and so the area under the curve is equal to 1 for both charts.

y = 1

y = 1 - 0.5x

In continuous probability distributions, probabilities are linked with intervals rather than single points and the probability of a single point is zero where

P(X = b) = 0 , thus P(a < X < b) = P(a < X < b)

Total area under a probability density function is 1 and for random variable X, with probability density function f(x) is represented as follows