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2021
In this final chapter we demonstrate some of the under-appreciated non-parametric tests. These are the cousins (not siblings) of the parametric ones. For example, if your dataset does not meet the assumptions for the t-test (parametric), then Mann-Whitney test (non-parametric) in this section can be an alternative for you.
Saiyidi Mat Roni +1 more
openaire +2 more sources
In this final chapter we demonstrate some of the under-appreciated non-parametric tests. These are the cousins (not siblings) of the parametric ones. For example, if your dataset does not meet the assumptions for the t-test (parametric), then Mann-Whitney test (non-parametric) in this section can be an alternative for you.
Saiyidi Mat Roni +1 more
openaire +2 more sources
2015
In parametric tests we generally assume a particular form of the population distribution (say, normal distribution) from which a random sample is drawn and we try to construct a test criterion (for testing hypothesis regarding parameter of the population) and the distribution of the test criterion depends upon the parent population.
Pradip Kumar Sahu +2 more
openaire +1 more source
In parametric tests we generally assume a particular form of the population distribution (say, normal distribution) from which a random sample is drawn and we try to construct a test criterion (for testing hypothesis regarding parameter of the population) and the distribution of the test criterion depends upon the parent population.
Pradip Kumar Sahu +2 more
openaire +1 more source
1972
In the last two chapters we have seen how the t-test can be used to derive confidence intervals and significance tests for an unknown mean. In this chapter we present some alternative methods of analysis which do not make the assumption that the observations are normally distributed.
openaire +2 more sources
In the last two chapters we have seen how the t-test can be used to derive confidence intervals and significance tests for an unknown mean. In this chapter we present some alternative methods of analysis which do not make the assumption that the observations are normally distributed.
openaire +2 more sources

