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Outlier is an observation which seems to deviate markedly from the other members of the sample in which it happens. In the set of systolic blood pressures, {125, 128, 130, 131, 198}, for instance, 198 might be considered an outlier. More formally the term refers to the observation which seems to be inconsistent with the rest of the data, relative to a supposed model. Such extreme observations might be reflecting some abnormality in the measured characteristic of the subject, or they might result from an error in the measurement or recording.
This graph for Cross Correlation Function for RES1, RES1 shows that there is possibly negative autocorrelation as there are alternating spikes; also the first spike is negative whi
Complier average causal effect (CACE): The treatment effect amid true compliers in the clinical trial. For the suitable response variable, the CACE is given by the difference in o
Paired availability design is a design which can lessen selection bias in the situations where it is not possible to use random allocation of the subjects to treatments. The desig
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
Independent component analysis (ICA) is the technique for analyzing the complex measured quantities thought to be mixtures of other more fundamental quantities, into their fundamen
The variables resulting from the recoding categorical variables with more than two categories into the sequence of binary variables. Marital status, for instance, if originally lab
An auditor for a government agency needs to evaluate payments for doctors' office visits paid by Medicare in a small regional town during the month of June. A total of 25,056 visit
Probability judgements : Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of o
Confidence profile method : A Bayesian approach to meta-analysis in which the information in each piece of the evidence is captured in the likelihood function which is then used al
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
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