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Discriminant analysis (DA) helps to determine which variables discriminate between two or more naturally occurring groups. Mathematically equivalent to MANOVA, it ' is extensively used when a set of explanatory variables are used to predict the group to which a given unit belongs (which is a nominal dependent variables). It cornhines the explanatory variables in order to create the largest F when the groups are used as a fixed factor in an ANOVA.
The model is constructed with a set of observations for which the classes are known. The set of observations are sometimes referred to as the training set.
Collect data about the chosen business problem or opportunity at the company. Explain how you obtained a suitable sample of either qualitative or quantitative data. Review data f
Q. Find relative maxima and minima? When finding relative maxima and minima in the Chapters absolute extrema problem, don't forget to use the first or second derivative test to
Assume that the normal distribution applies and find the critical z value(s). A = 0.04; H1 is mean ≠ 98.6 degrees Fahrenheit. Dteremine the value of Z. Find the value of the
Assumption of extrapolation
For the following questions we are interested in a comparison of the 16 years education vs. > 16 years. (Recall we did the analysis on the log scale, so these are actual means on t
i m doing MBA in singapore and i want a good work. i want a data for 200 observations and then answers for some questions. and i need the data to be approved by our professor first
Convenience Sampling It means a convenient sample is obtained by selecting convents units from the universe. Convenient sample is also known as chunk. It means a fraction of
Q. 1 a) Describe the important quantitative techniques used in public system management. (10) b) Do you think the day will come when all decisions are made with the assistance of
how many types of ogive are there
1. Recognize and explain the opportunities for statistical learning. 2. Describe how the use of statistics supports student learning. 3. Recognize appropriate data displays a
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