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Fill up : In a symmetrical binomial dist...

Fill up : In a symmetrical binomial distribution, p = ___.

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If n and p are two parameters of a binomial distribution, state which one of the following is not true -

In a symmetric distribution, the mean and the mode are

State True/False : The parameter p and n completely determine a binomial distribution.

If n and p are two parameters of binomial distribution then its standard deviation is -

If the sum of the mean and variance of a binomial distribution for 5 random trials is 1.8 then find the binomial distribution.

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UNITED BOOK HOUSE-MODEL QUESTION PAPERS SET-07-Exercise
  1. Fill up : If b(xy) =-0.09 and b(yx) = -0.4 then r(xy) = .

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  2. Fill up : The point of intersection of two regression lines give the.

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  3. Fill up : An over all rise or fall in a time series is called the.

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  4. Fill up : In a trend equation y = a + bx, a is the and b represents t...

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  5. Fill up : A polynomial of the form y = a + bx + cx^2 is called a .

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  6. Fill up : In a symmetrical binomial distribution, p = .

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  7. Fill up : In a normal distribution, the value of 3rd order central mom...

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  8. State True/False : The variance of binomial distribution can never exc...

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  9. State True/False : For nornial distribution, the co-efficient of skewn...

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  10. State True/False : The parameter p and n completely determine a binomi...

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  11. State True/False : The correlation co-efficient x and y is 0.5, then b...

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  12. State True/False : The two regression equations coincide when r = +- 1...

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  13. State True/False : If Cov (x, y) = 0, then x and y are independent.

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  14. Short Questions: What will be r(xy) if the two regression lines are co...

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  15. Short Questions: Calculate the means of the variables x and y, given t...

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  16. Short Questions: Short notes: (i) Secular trend (ii) method of moving ...

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  17. Short Questions: The p.m.t. of a r.v.x. is given by f( x) = K.x^2, x= ...

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  18. Short Questions: For a poisson distribution, P[x = K] = P[x=K+1], Find...

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  19. Textual Questions: Explain different components of a time series.

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