# ISS Statistics Paper I (Old Subjective Pattern): Questions 59 - 64 of 165

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## Question number: 59

» Statistical Methods » Tests of Significance » Chi-Square

Appeared in Year: 2010

### Describe in Detail

For 2X2 table

A | b |

C | d |

prove that Chi-square test of independence gives

### Explanation

Let the contingent table is

Class | A | α | Total |

B | a | b | a + b |

β | c | d | c + d |

Total | a + c | b + d | a + b + c + d =N |

Here A denotes the presence of any attributes and α denotes the absence of… (453 more words) …

## Question number: 60

» Probability » Standard Probability Distributions » Uniform

Appeared in Year: 2010

### Describe in Detail

Let X be a random variable with a continuous distribution function F. Show that F (X) has the uniform distribution on (0, 1).

### Explanation

Let U = F (x), then the distribution function of G of U is given by

The… (93 more words) …

## Question number: 61

» Probability » Standard Probability Distributions » Cauchy

Appeared in Year: 2012

### Describe in Detail

For the Cauchy distribution given by

where k is a constant to be suitably chosen, derive the expression for the distribution function. Hence obtain a measure of central tendency and a measure of dispersion. What are the points of inflexion of the distribution?

### Explanation

We choose k as constant that gives the integral over the range x for the density function is equal to one.

… (381 more words) …

## Question number: 62

Appeared in Year: 2011

### Describe in Detail

A fair die is thrown until a 6 appears. Specify the sample space. What is the probability that it must be thrown at least 3 times?

### Explanation

A fair die content the value {1, 2, 3, 4, 5, 6}

So, the probability of getting 6 is p = 1/6, then probability of getting other than 6 is q = 5/6

If we throw a die, the six is appear. Then the probability is p and the experiment… (162 more words) …

## Question number: 63

» Probability » Conditional Probability

Appeared in Year: 2011

### Describe in Detail

Consider the following bivariate p. m. f. of (X, Y):

p (0, 10) = p (0, 20) = 2/18;

p (l, 10) = p (l, 30) = 3/18;

p (1, 20) = p (2, 30) = 4/18;

Obtain the conditional mass functions p (y lx = 2), and p (y lx = 1).

### Explanation

The joint probability is given

- | x | Total | |||

- | 0 | 1 | 2 | ||

Y | 10 | 2/18 | 3/18 | 0 | 5/18 |

20 | 2/18 | 4/18 | 0 | 6/18 | |

30 | 0 | 3/18 | 4/18 | 7/18 | |

Total | 4/18 | 10/18 | 4/18 | 1 |

First find the marginal probability of x at x = 0, 1, 2

… (136 more words) …

## Question number: 64

» Statistical Methods » Bivariate Distributions » Bivariate Normal Distribution

Appeared in Year: 2014

### Describe in Detail

The marginal distributions of X and Y are given in the following table:

X | 1 | 2 | Total | |

Y | 3 4 | ? ? | ? ? | 1/4 3/4 |

Total | 1/2 | 1/2 | 1 |

If the co-variance between X and Y is zero, find the cell probabilities and see whether X and Y are independent.

### Explanation

Given that covariance between X and Y is zero

This gives that f (xy) =f (x) f (y)

So, the joint probability density function of… (168 more words) …