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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.
Assume that a simple random sample has been selected from a normally distribute population and test the given claim. Identify the null and alternative hypotheses, test statistic,
In New Jersey, banks have been charged with withdrawing from counties having a high percentage of minorities. To substantiate this charge, data is presented in the table below conc
Cluster Analysis could be also represented more formally as optimization procedure, which tries to minimize the Residual Sum of Squares objective function: where μ(ωk) - is a centr
Types of business forecasting are generally as follows: 1. Sales and Demand forecasts 2. Porduction forecasts. 3. Cost Forecasts 4. Financi
Factor analysis (FA) explains variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are expressed in
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
Using the raw measurement data presented below, calculate the t value for independent groups to determine whether or not there exists a statistically significant difference between
Lorenz Curve It is a graphic method of measuring dispersion. This curve was devised by Dr. Max o Lorenz a famous statistician. He used this technique for wealth it i
ogives graph
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
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