Statistical Fallacies Assignment Help
Statistics are convincing and this has led many people to believe that they can be accepted without question. However, this is a false notion as misuses are probably as common as valid uses of statistics. The figures provide only raw material for someone to reason from-they seldom. If ever, speak for them, i.e. they have to be interprets. According to studydaddy the inter-predation if data is a very difficult task and requires a high degree or skill Care judgment and objectivity. In the absence of these, there is every likelihood of the data being misused to prove things that are not at all true. In fact experience shows that the largest number of mistakes is committed consciously or unconsciously while interpreting statistical data and vey offer facts and figures are presented in such a manner that they are misinterpreted by most of the readers.
It should be noted that the motive or inert of the misuse of statistics is not at issue: fallacies designed to mislead and those committed unintentionally will not be distinguished. According to free answers service the effect is the same in both the cases although, to be sure, in the first case there is abuse of statistics and in the second case only a misuse.
Statistical fallacies may arise in collection, presentation, analysis and interpretation of data. The following are some of the specific examples illustrating how statistics can be misinterpreted of how fallacies arise in using statistical data and statistical methods.
According to math homework help some of its main topics are:
1. Introduction to statistical fallacies2. Technical errors3. Inconsistency in definitions4. Failure to comprehend the total background of the data5. Faulty deductions
Experimental Designs Assignment Help
The first great stimulus to the development of the theory and practice of experimental design came from agricultural research. R.A Fisher realized that current practice in field plot trials failed to produce unambiguous conclusions. This led him from about 1923 onward to examine the principles underlying scientific experimentation and to evolve new techniques of design. Not only was it necessary to devise procedures that would permit design. Not only was it necessary to devise procedures that would permit the drawing of valid inferences from experimental results, but these inferences has to freed as far as possible from the obscuring effect of the variability inherent in the material and the nature of the observations. Not only was randomization needed in order to remove bias, but also for making valid estimates of standard errors. The labour of performing experiments and the number of questions requiring investigation were so great as to make imperative techniques that should use most effectively the materials and effort employed and should give results of high precision. To fisher goes most of the credit for stating and solving these problems and creating a new branch of science from which experimentation in many fields of research has since benefitted. Although this science of experimental design is today used widely in biology and elsewhere, the standard nomenclature retains evidence of its agricultural origin.
Some of its main topics are:
1. Randomized blocks vs Latin square2. Latin square3. Computation of trend values4. Trends