By Pradip Kumar Sahu
This e-book is aimed toward a variety of readers who lack self assurance within the mathematical and statistical sciences, really within the fields of Agriculture, Veterinary, Fishery, Dairy and different comparable components. Its objective is to give the topic of information and its worthwhile instruments in a number of disciplines in this kind of demeanour that, after studying the booklet, readers can be outfitted to use the statistical instruments to extract differently hidden info from their info units with self belief. beginning with the that means of records, the publication introduces measures of valuable tendency, dispersion, organization, sampling equipment, likelihood, inference, designs of experiments and plenty of different matters of curiosity in a step by step and lucid demeanour. The correct theories are defined intimately, through a extensive diversity of real-world worked-out examples, solved both manually or with the aid of statistical applications. In final, the ebook additionally contains a bankruptcy on which statistical applications to exploit, reckoning on the user’s respective requisites.
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Extra info for Applied Statistics for Agriculture, Veterinary, Fishery, Dairy and Allied Fields
3 Harmonic Mean Harmonic mean of a set of “N” observations X1, X2,X3,. ,Xi,. ,XN is defined as the “the reciprocal of the arithmetic mean of the reciprocals of the observations”. 0 x2 f1 f2 x3. , xi,. xnÀ2 f3. , fi,. 0 to find the harmonic mean of the above fish weights. H:M: ¼ x1 . 7 Solution Here the number of observations is 20. , the arithmetic mean and geometric mean, the harmonic mean is also defined clearly; it is also based on all observations but comparatively complicated in calculation and understanding.
4). As because we are dealing with only 60 data points (observations), it is relatively easy to understand the data characters. But when dealing 15 with a huge number of data points, then we are to think for further processing of data. So the next objective will be to study the feasibility of forming groups/classes of elements (birds) which are more or less homogeneous in nature with respect to body weight. 5 Classification/Grouping Classification refers to grouping of large number of observations into relatively fewer groups so that an instant idea is obtained seeing the groups.
Cumulative frequency divides the entire range of data set into different component as per the requirement of the investigator. Cumulative frequency is of two types: cumulative frequency less than type and cumulative frequency greater than type. Cumulative frequency less than type is the total number of observations below a particular value; it generally corresponds to the upper boundary of different classes. 5 g. On the other hand, cumulative frequency greater than type is the total number of observations equals to or above a particular value; it generally corresponds to the lower Data–Information and Its Presentation boundary of different classes.
Applied Statistics for Agriculture, Veterinary, Fishery, Dairy and Allied Fields by Pradip Kumar Sahu