Continuous probability distribution

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SUMMARY

The discussion centers on the calculation of the probability density function (pdf), mean, and variance for a continuous random variable X representing the duration of a telephone call. The cumulative distribution function (cdf) is defined as F(x) = x²/8 for 0 ≤ x ≤ 2 and F(x) = 1 - 4/x³ for x > 2. The derived pdf is f(x) = 1/4 x for 0 ≤ x ≤ 2 and f(x) = 12/x⁴ for x > 2. The calculated mean E(X) is 20/3, while the variance calculation results in a negative value, indicating a potential error in the computations.

PREREQUISITES
  • Understanding of continuous probability distributions
  • Familiarity with cumulative distribution functions (CDFs)
  • Knowledge of probability density functions (PDFs)
  • Basic calculus for integration and expectation calculations
NEXT STEPS
  • Review the derivation of probability density functions (PDFs) from cumulative distribution functions (CDFs)
  • Study the properties of variance and conditions for valid variance calculations
  • Learn about integration techniques for calculating expected values in continuous distributions
  • Examine common pitfalls in probability calculations, particularly in variance determination
USEFUL FOR

Students studying probability theory, statisticians, and anyone involved in data analysis or mathematical modeling of continuous random variables.

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Homework Statement



A continuous random variable ,X represents the period, of a telephone call in the office. The cdf of x is given by

F(x)= x^2/8 for 0<=x<=2

=1-4/x^3 for x>2

Find pdf , mean and variance.

Homework Equations





The Attempt at a Solution



pdf:

f(x) = 1/4 x for 0<=x<=2

=12/x^4 for x>2

= 0 , otherwise

[tex]E(x)=\int^{2}_{0}x(\frac{1}{4})x dx +\int^{\infty}_{2}x(\frac{12}{x^4})dx[/tex]

=20/3

[tex]E(x^2)=\int^{2}_{0}x(\frac{1}{4})x^2 dx +\int^{\infty}_{2}x^2(\frac{12}{x^4})dx[/tex]

=7

Var(x)=7-(20/3)^2

Variance is negative here , how can that be? I have checked my working thoroughly but am not able to spot my mistakes.
 
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Check your calculation of [tex]E(X)[/tex] once again - I get a different value.
 

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