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Disclosure risk, The risk of being able to recognize the respondent's confi...

The risk of being able to recognize the respondent's confidential information in the data set. Number of approaches has been proposed to measure the disclosure risk some of which c

Outliers - reasons for screening data, Outliers - Reasons for Screening Dat...

Outliers - Reasons for Screening Data Outliers are due to data entry errors, subject is not a member of the population that the sample is trying to represent, or the subject i

Explain missing values, Missing values : The observations missing from the ...

Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud

Construct a stem-and-leaf diagram, The number of employees absent from work...

The number of employees absent from work at a large electronics manufacturing plant over aperiod of 106 days is given in the table below. 146 141 139 140 145 141 142 131 142 140

Mortality odds ratio, Mortality odds ratio  is the ratio equivalent to the ...

Mortality odds ratio  is the ratio equivalent to the odds ratio used in case-control studies where the equivalent of the cases are deaths from the cause of interest and the equival

Glejsers test, The Null Hypothesis - H0:  There is no heteroscedasticity i....

The Null Hypothesis - H0:  There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1 0 Reject H0 if |t | > t = 1.96

Indirect standardization, Indirect standardization is the procedure of adju...

Indirect standardization is the procedure of adjusting the crude mortality or morbidity rate for one or more variables by making use of a known reference population. It may, for in

Leaps-and-bounds algorithm, Leaps-and-bounds algorithm is an algorithm whi...

Leaps-and-bounds algorithm is an algorithm which is used to ?nd the optimal solution in problems which might have a large number of possible solutions. Begins by dividing the poss

Principal factor analysis, Principal factor analysis is the method of fact...

Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl

Regression analyze, I do have a data of real gdp for each state and from 20...

I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try

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