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Andrews ‘Plots
A graphical display of multivariate data in which an observation, x0 = [x1, x2, . . . , xq] is represented can be represented in the form of function
A set of the multivariate observations is then displayed as the collection of these kind of plots and it can be shown that those functions which remain close together for all values of t correspond to the observations which are close to one another in the terms of their Euclidean distance. This property states that such plots can often be used to detect groups of similar observations and identify outliers in multivariate data both. The example given in the Fig drawn below consists of plots for the sample of 30 observations each of which having five variable values.
The plot signifies the presence of three groups in the data. These type of plots can cope only with a reasonable number of observations before becoming very complicated to unravel.
(a) At a stream gauging station, the following discharges and stage measurements were taken for the purpose of the rating curve at that section: Stage (m) 1
Test for Equality of Proportions For example, we may want to test whether the percentage of smokers (p 1 ) among the males equals the percentage of female smokers (p 2 ). W
Statistician is searching the \home ground" effect and is studying 20 football games, of which 14 were won by the home team and 6 by the visitors. Therefore the game is a Bernoulli
Consider three stocks A, B and C costing $100 each. The annual returns on the three stocks have mean $5 and variance $10. a. Suppose that the returns on the three stocks are i.i
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The box plot displays the diversity of data for the age; the data ranges from 19 being the minimum value and 60 being the maximum value. The box plot is positively skewed at 0.57 a
Question: (a) (i) Define the term multicollinearity. (ii) Explain why it is important to guard against multicollinearity. (b) (i) Sometimes we encounter missing values
There are two diagnostic tests for a disease. Among those who have the disease, 10% give negative results on the first test, and independently of this, 5% give negative results on
Assumptions in Regression To understand the properties underlying the regression line, let us go back to the example of model exam and main exam. Now we can find an estimate o
Theories of Business forecasting
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