By S. P. Venkateshan

The 1st variation of this ebook was once co-published by means of Ane Books India, and CRC Press in 2008. This moment variation is an enlarged model of the net path constructed by way of the writer at IIT Madras, and in addition a changed and augmented model of the sooner ebook. significant additions/modifications offered are within the remedy of error in size, temperature size, dimension of thermo-physical houses, and information manipulation. Many new labored examples were brought during this new and up to date moment version.

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370. 392 we conclude that there are no more abnormal data. Step 5 We discard the two abnormal data found above and end up with a sample containing 17 data points. 170. Step 6 We would like to check if a single data is abnormal in the reduced set obtained by discarding the outliers found previously. 134 for n = 17 and one abnormal data. 362. We calculate absolute values of all the 17 deviates and pick the maximum value. The maximum value is found to correspond to student No. 372. 362 we discard this data.

58 = 256 where the denominator 256 represents total number of possible ways of getting all possible combinations of outcomes when 8 experiments are performed. Thus we have the binomial distribution function B(k; n, p) = n! (n − k)! where n and p are indicated as parameters, by placing them after a semicolon following k. The expression given above is one of the terms in the binomial 1 [p + (1 − p)]n . 5) = n! (n − k)! 5) = 1. 3. Statistical analysis of experimental data 11 For sufﬁciently large n the Binomial distribution is closely approximated by the Normal distribution or the Gaussian curve.

Statistical analysis of experimental data 13 Variance of the means The problem is posed as given below: • • • • Replicate data is collected with n measurements in a set or a sample Several (possibly) such sets of data are collected Sample mean is m s and sample variance is σ2s What is the mean and variance of the mean of all samples? Population mean: Let N be the total number of data in the entire population, if indeed, a large number of samples have been collected. Without loss of generality we assume that the population mean is zero.