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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.
Old Faithful Geyser in Yellowstone National Park derives its names and fame from the regularity (and beauty) of its eruptions. Rangers usually post the predicted times of eruptions
Theories of Business forecasting
1. Use the concepts of sampling error and z-scores to explain the concept of distribution of sample means. 2. Describe the distribution of sample means shape for samples of n=36
#question HOW TO TEST
TYPE I AND II Errors If a statistical hypothesis is tested, we may get the following four possible cases: The null hypothesis is true and it is accepted; The
(a) Elevation (m) 0 400 800 1200 1600 2000 2400 2800 3200 4000 480
Differentiate between data and database
The Neatee Eatee Hamburger Joint specializes in soyabean burgers. Customers arrive according to the following inter - arrival times between 11.00 am and 2.00 pm: Interval-arriva
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
Binomial Distribution Binomial distribution was discovered by swiss mathematician James Bernonulli, so this distribution is called as Bernoulli distribution also, this is a d
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