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Jonckheere Terpstra test is the test for detecting particular types of departures from the independence in a contingency table in which both the row and column categories contain the natural order (it is the doubly ordered contingency table). For instance, assume the r rows represent r distinct drug therapies at the progressively increasing drug doses and the c columns represent the c ordered responses. Interest in this case may centre on detecting the departure from independence in which drugs administered at larger doses are much more responsive than the drugs administered at smaller ones.
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
Primary Model Below is a regression analysis without 17 outliers that have been removed Regression Analysis: wfood versus totexp, income, age, nk The regression equat
Collapsing categories : A procedure generally applied to contingency tables in which the two or more row or column categories are combined, in number of cases so as to yield the re
Resentful demoralization is the possible phenomenon in the clinical trials and intervention studies in which comparison groups not attaining a perceived desirable treatment become
PRINCIPLES OF MODELLING IN OR.
Kolmogorov Smirnov two-sample method is a distribution free technique which tests for any difference between the two populations probability distributions. The test is relied on t
difference between histogram and historigram
Median absolute deviation (MAD) : It is the very robust estimator of the scale given by the following equation or, in other words we can say that, the median of the absolute
Hot deck is a method broadly used in surveys for imputing the missing values. In its easiest form the method includes sampling with replacement m values from the sample respondent
The Null Hypothesis - H0: There is autocorrelation The Alternative Hypothesis - H1: There is no autocorrelation Rejection Criteria: Reject H0 (n-s)R 2 > = (1515 - 4) x (0.
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