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- Descriptive statistics
- Measures of central tendency
- Measures of dispersion
- Correlation and regression
- Curve fitting
- Permutation and combination
- Probability
- Random variables
- Theoretical probability distribution
- Inference
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Our examples below illustrate our comprehensive explanations with all steps. This means: Better understanding and Greater success in Statistics for YOU
| 1. |
In a probability distribution if P(X = 2) = P(X = 3), then find P(X =4)
Given P(X = 2) = P(X = 3)
Let X: a Poisson variate.
The probability mass function is given by P(X= x) =
Then,
Therefore,
Therefore,
Thus in a probability distribution, if P(X = 2) = P(X = 3), then P(X =4) =0.1681.
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2. |
Team A has probability  of winning whenever it plays.
If it plays four games, find the probability that it wins
- 2 games
- At least one game.
Let 'X' be the number of games A wins. Then X is given by
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It is given |
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Therefore,
(i) 
(ii) 
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| 3. |
Six dice are thrown 729 times. How many times
will at least three of the six dice show 5 or 6?
Therefore,
Here the binomial distribution is N. P(x), and N - the number of trials is 729
Since there are six dice, for at least three dice to show 5 or 6, we have the chances as 3 times 5 or 6, 4 times 5 or 6, 5 times 5 or 6, 6 times 5 or 6.
Therefore,
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