134 revision points 1 the hypothesis of a non

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13.4. REVISION POINTS 1) The hypothesis of a non-parametric test are concerned with something other than the value of a population parameter. 2) Rank sum tests depends on the ranks of the sample observations. 3) We will use the Mann-Whitney test when only two populations are involved and Kruskal Wallis test when more than two populations are involved. 4) A run is a sequence of identical occurrences proceed and followed by different occurrences.
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109 13.5. INTEXT QUESTIONS 1) What do you understand by non-parametric statistical test ? 2) Give a list of all non-parametric tests you know. 3) What is meant by distribution free statistical tests ? which is the most popular non-parametric statistical test and why ? 4) What are the advantages and disadvantages of the use of non-parametric tests ? 5) Describe the role of ordered statistics in non-parametric tests. 13.6. SUMMARY Non-parametric tests do not require any information whatsoever about the specific form which the population distribution should process The only requirement for these tests to be applicable is that the population distribution should be continuous. As the actual population distribution (normal) is of non- consequence for the application of non-parametric tests, these tests are also designated as distribution free testing methods. The term non-parametric does not imply the population distribution has no parameters, for all populations do possess the basic parameters which define their distribution. 13.7. TERMINAL EXERCISES Short Answer Questions 1) What do you mean by distribution free methods? 2) What is the most characteristic feature of data for which non-parametric test is used? 3) Write a note on the advantages and disadvantages of non-parametric methods. 4) When are Non-parametric tests used? 5) When should the non-parametric methods be preferably used? Objective Questions 1) When compared to parametric methods, non-parametric methods. a) Are less accurate b) Are less efficient c) Are computationally easier d) All of these. 2) Non-Parametric methods are based on. a) Mild assumptions b) Stringent assumptions c) No assumptions d) None of the above 3) Most of the non-parametric methods utilse measurements on a) Interval scale b) Ratio scale c) Ordinal scale d) Nominal scale
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110 4) Ordered statistics is a sequence of a) Observations b) Ranks c) Natural numbers d) Integers 5) Most commonly used assumption about the distribution of variable is a) Continuity of the distribution b) Symmetry of the distribution c) Both (a) and (b) d) Neither (a) nor (b) 13.8. SUPPLEMENTARY MATERIALS 1) 2) 3) 4) - statistics 13.9. ASSIGNMENTS 1) Discuss the situations where only non-parametric tests can be applied.
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