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Lorenz curve: Essentially the graphical representation of cumulative distribution of the variable, most often used for the income. If the risks of disease are not monotonically increasing as the exposure becomes heavier, the data have to be arranged again from the lowest to the highest risk before the calculation of cumulative percentages. Associated with such type of curve is the Gini index defined as twice the area between curve and diagonal line. This index is lies between zero and one, with the larger values indicating the larger variability while smaller ones signify larger uniformity. The further the Lorenz curve lies below line of equality, the more unequal is the distribution of, the figure for this is given below
Histogram is the graphical representation of the set of observations in which class frequencies are represented by the regions of rectangles centred on the class interval. If the f
when there is tie in sequencing then what we do
Quittingill effect is a problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms
Regression line drawn as y= c+ 1075x ,when x was2, and y was 239,given that y intercept was 11. Calculate the residual ?
Briefly explain the importance of forecasting for managers?
Atomistic fallacy : A fallacy which arises because of the association between two variables at the individual level might vary from the association between the same two variables m
Kendall's tau statistics : The measures of the correlation between the two sets of rankings. Kendall's tau itself (τ) is the rank correlation coefficient based on number of inversi
The graphical process most frequently used in the analysis of data from a two-by-two crossover design. For each of the subject the difference between the response variable values o
The problem that the studies are not uniformly probable to be published in the scientific journals. There is evidence that the statistical significance is a main determining factor
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
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