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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.
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
In a study of outcomes for patients who had been in the Intensive care Unit (ICU) at a large hospital, the records from last 150 patients who had been in the ICU for more than one
Accelerated Failure Time Model A basic model for the data comprising of survival times, in which the explanatory variables measured on an individual are supposed to act multipli
Question: The weights of 60 children born to mothers in a small rural hospital were recorded. 3.63 3.54 3.15 3.90 4.29 4.06 2.91 3.36 3.3
Methods of Forecasting Various techniques which are generally used in business forecasting are as under: 1. Forecasting through the opinion of heads of department
Level of Significance: α The main purpose of hypothesis testing is not to question the computed value of the sample statistic, but to make judgment about the difference between
A salesperson visits from house to house to sell her knives. The probability that she makes a sale at a random house is .3. Given that she makes a sale, the sale is worth $100 with
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Cause and Effect Even a highly significant correlation does not necessarily mean that a cause and effect relationship exists between the two variables. Thus, correlation does
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