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Correspondence analysis is an exploratory technique used to analyze simple two-way and multi-way tables containing measures of correspondence between the rows and colulnns of any given data. The results provide information almost similar to those produced by Factor Analysis techniques, and they allow us to explore the structure of categorical variables included in the table. Multiple correspondence analysis (MCA) is an extension of simple correspondence analysis to more than two variables. MCA can be used to analyze several contingency tables by generalizing CA.
two application of statistics
Grouped data For grouped data, the formula applied is σ = Where f = frequency of the variable, μ= population mea
A researcher was interested lowering the high school dropout level in his county. He measured the reading level of students entering middle school (based on a standard test) and th
If the test is two-tailed, H1: μ ≠ μ 0 then the test is called two-tailed test and in such a case the critical region lies in both the right and left tails of the sampling distr
Consider the following linear regression model: a) What does y and x 1 , x 2 , . . . . x k represent? b) What does β o , β 1 , β 2 , . . . . β k represent?
The PCA is amongst the oldest of the multivariate statistical methods of data reduction. It is a technique for simplifying a dataset, by reducing multidimensional datasets to lower
Systematic Random Sampling This method is generally used in such cases where a complete list of the population is available from which sample has to be selected. Under this
Analytical Approach We will illustrate this through an example. Example 1 A firm sells a product in a market with a few competitors. The average price charged by the
how can i use continuous frailty in multi state models?
Frequency distribution A frequency distribution is a series where a number of items with similar values are put in separate groups or bunches. In other words a frequency distri
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