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Page 7

This suggests to us another way of measuring the probability of an event : by

counting the number of times the event ...

event Probability = :

performs a ...

This suggests to us another way of measuring the probability of an event : by

counting the number of times the event ...

**Total number**of occurrences of theevent Probability = :

**Total number**of trials Thus, for example, if a surgeonperforms a ...

Page 67

M. J. Moroney. Now, instead of finding the

) and dividing this

4- 1 , we might proceed as follows : (2xl) + (4x2)+(3x3)+(4x4) + (2x5)+(2x6) + ...

M. J. Moroney. Now, instead of finding the

**total**of the items in the original list (=82) and dividing this

**total**by the**number**of items (« = 20) to get the average value =4- 1 , we might proceed as follows : (2xl) + (4x2)+(3x3)+(4x4) + (2x5)+(2x6) + ...

Page 378

In order to get the Between Sample Sum of Squares, we find the sum of the

squares of the sample totals and divide this sum by the

went to make up each sample

this way ...

In order to get the Between Sample Sum of Squares, we find the sum of the

squares of the sample totals and divide this sum by the

**number**of items whichwent to make up each sample

**total**Finally, we subtract the Correction Factor. Inthis way ...

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### Contents

The Normal Distribution | 108 |

What Happens when we take Samples | 120 |

Control Charts | 141 |

Copyright | |

12 other sections not shown

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### Common terms and phrases

Analysis of Variance arithmetic arithmetic mean average value batch Binomial Binomial distribution block calculate chance Chapter column computation consider control chart control limits Correction Factor correlation coefficient degrees of freedom denote difference distribution effect entry equal equation example experimental following table formula frequency give given grand average graph height inoculated inspection Intelligence Quotient judges loss angles mean value measure median method Normal Curve Null Hypothesis number of defectives number of degrees number of items pairs Percent Defective percentage plots Poisson Poisson distribution population possible predicted prob probability problem proportion quantity R. A. Fisher range rank total reader regression replication Residual Risk sample mean sampling scheme significant small samples standard deviation standard error statistical statistician Subtract Sum of Squares Suppose technique things tion total number Total Sum treatment trend variable variance estimate variation yields