Statistics Assignment Help With Tests Of Significance
A very important aspect of the sampling theory is the study of the tests of significance, which enable us to decide on the basis of the sample results, if
- The deviation between the observed sample statistic and the hypothetical parameter value, or
- The deviation between two independent sample statistics:
Is significant or might be attributed to chance or the fluctuations of sampling is significant or might be attributed to chance or the fluctuations of sampling.
Since, for large n, almost all the distributions, eg., Binomial, Poisson, Negative binomial, Hyper geometric, t, F, chi square can be approximated very closely by a normal probability curve, we use the normal test of significance for large samples. Some of the well known tests of significance for studying such differences for small samples are t-test, F-test and Fisher’s z –transformation.
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Following are some of the topics in Sampling and Large Sample Tests in which we provide help:
- Procedure for testing of hypothesis
- Test Of Significance For Large Samples
- Sampling Of Attributes
- Test of significance for difference of proportions
- Sampling of Variables
- Standard Error Of Sample Mean
- Test Of Significance For Single Mean
- Test Of Significance For Difference Of Means
- Test Of Significance For The Difference Of Standard Deviations
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