Do parametric and non-parametric tests share any of the same characteristics?
492382
Here ya go! Do a little research and the answer will be obvious.
2775
They are not inconsistent. They have a solution (x,y)=(0,4). \n\nThey are not dependent, since one is not a multiple of the other. \n\nThey are independent.
438145
Chisq test for proportional differences or a One-way Chi-sq same thing though.  The difference in your proportions +/- 1.96 x standard error.
685395
Depends on the situation.\n\nFor example, you want to decide whether a batch of products is defective.  If your test come out to be significant but actually not (type I error), you have thrown away a perfectly fine batch of products.\n\nOn the other hand, for the same batch of products, if your test come out to be not significant but actually the batch is defective (type II error), then you have accepted a bad lot of products. \n\nSo in summary, type I error wastes money, type II error saves money but consumers don't like it.  Use similar analysis in your case.
197629
"Omnibus" does not have a special meaning in this case.  As in regular english, it means "providing for many things at once."\n\nMany statistical tests only test one aspect.  For example, normality may be tested by determining whether the skewness of a distribution is within the range expected for a normal distribution.\n\nAn "omnibus test" tests more than one thing.  For example, an omnibus test of normality might require that both skewness and kurtosis be within the ranges expected for a normal distribution.
231717
I haven't heard of it. My attitude toward it, however, is to find out WHAT the actual tests consisted of. Though people test products all the time, it does not mean that they tested in a way that could possibly be accurate.
917250
I'm going off memory here so be sure to check this.  I think the formula is the same, but the structure may be different.  Just trying to point you in the right direction.
905883
For each object some test cases can be put for both positive and negative testing under the white and block box based methodologies.... and all wud be based upon the functionality thats intended of the object... (since thats not specified... it not possible to highlight more upon what they can be)... for various phases... integration,development... based on the V model.
857058
Check this Link:\n\nhttp://www.bredemeyer.com/pdf_files/NonFunctReq.PDF
915189
To my knowledge, there is no min sample size.  In fact, that is one reason K-S might be used, in that Chi Square g-o-f tests can require a relatively larger sample size.
251100
Yes!\n\nExperimental designs are efficient strategies for designing experiments using a minimum number of runs while enabling a maximum number of factors or parameters to be tested simultaneously. They also facilitate the statistical data analysis phase and the interpretation of results.\nCovers fundamental statistical methods for the Design of Experiments (DOE): accounting for various sources of variability, tools for minimizing and controlling variability, the comparison of two groups, the comparison of more than two groups, the Student's t-test, the Analysis of Variance (ANOVA), and the techniques of multiple comparisons for locating statistical differences.\n\n\nOne Way Analysis of Variance\n\nThe one way analysis of variance allows us to compare several groups of observations, all of which are independent but possibly with a different mean for each group. A test of great importance is whether or not all the means are equal.\n\n*********************\n\nThe observations all arise from one of several different groups (or have been exposed to one of several different treatments in an experiment). We are classifying 'one-way' according to the group or treatment.\n\n\nBasically ANOVA is just one tool to use, not unlike a t-test and design of experiments we are concerned with the analysis of data generated from an experiment. It is wise to take time and effort to organise the experiment properly to ensure that the right type of data, and enough of it, is available to answer the questions of interest as clearly and efficiently as possible. \n\nThe specific questions that the experiment is intended to answer must be clearly identified before carrying out the experiment. We should also attempt to identify known or expected sources of variability in the experimental units since one of the main aims of a designed experiment is to reduce the effect of these sources of variability on the answers to questions of interest. That is, we design the experiment in order to improve the precision of our answers.\n\nTreatment\n\nIn experiments, a treatment is something that researchers administer to experimantal units . For example, a corn field is divided into four, each part is 'treated' with a different fertiliser to see which produces the most corn; a teacher practices different teaching methods on different groups in her class to see which yields the best results; a doctor treats a patient with a skin condition with different creams to see which is most effective.\n\n*********************\n\nTreatments are administered to experimental units by 'level', where level implies amount or magnitude. For example, if the experimental units were given 5mg, 10mg, 15mg of a medication, those amounts would be three levels of the treatment. 'Level' is also used for categorical variables, such as Drugs A, B, and C, where the three are different kinds of drug, not different amounts of the same thing.\n\nFactor\n\nA factor of an experiment is a controlled independent variable; a variable whose levels are set by the experimenter.\n\n*********************\n\nA factor is a general type or category of treatments. Different treatments constitute different levels of a factor. For example, three different groups of runners are subjected to different training methods. The runners are the experimental units, the training methods, the treatments, where the three types of training methods constitute three levels of the factor 'type of training'.
846910
No. They do not share the same dimensions.\n\nYou can multiply them though.
111164
That is an assumption which cannot be proven. No one yet disproved it by showing 2 of the same.\n\nIf you consider the molecular scale, there's pretty much never 2 of the same of anything.  So I (as most people seem to) am referring to 2 of the exact same pattern.  There are infinitely many of possibilities, but there have been an awful lot of snowflakes to assume none have been the same.
359986
Student's t-test can be used to determines the probability that 2 random variables have the same mean. This can then be used to test whether two sets of data come from the same source.
248449
If you suspect that scores are not the same within two groups, you must place this statement in the alternative hypothesis.\n\nHo=scores are same\nHa=scores are not the same.\n\nBy claiming this this way, you can test it using the in formation obtained from the sample data and conclude whether or not data is sufficient to claim that you can reject the null hypothesis, and decide that scores are not the same. Always, you must place a new claim, a new suspicion in the alternative hypothesis, so that you can reject the null and conclude Ha, or you can not reject and conclude that you have not enough evidence to claim Ha.
930901
No they are different chemicals...;
299127
You need to be more specific.\n\nHowever:\nThere are secondary variables - unintentional variations other than those variable you are testing.  The way to avoid this, such as noise, is to either find a way to eliminate it or make it uniform.\n\nA large sample size will make an experiment more accurate.\n\nDouble-blind studies (one where the research assistant administering the test does not know what is being tested for and therefor cannot influence the results) are good.\n\nIn any case, I cannot really answer further unless I know more about the study.