List  I List II (a) The ability to test to reject the null hypothesis when it is false (i) Level of significance (b) The probability of accepting a false null hypothesis (ii) Type I error (c) The probability of rejecting a true null hypothesis (iii) Type II error (d) The probability of rejecting a […]

Statement I: The absolute value of the difference between an unbiased estimate and the corresponding population parameter is called sampling error. Statement II: Multi-stage sampling is a restricted non-probability based sampling technique.  

List-I                                                                                      List-II (a)Contingency coefficient for any size of                                   (i)   N-n Contingency table                                                                             N-1   (b) Statistical approach […]

Statement-I: Non-parametric tests are based on some assumptions about the parent population from which the sample has been drawn. Statement-II: The standard deviation of the sampling distribution of mean is called standard error of mean.  

Statement-I: When the null hypothesis is true but as per the hypothesis-testing, it is rejected, it is known as beta type error in hypothesis testing Statement-II: Chi-square test is exclusively a non-parametric test.