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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.
In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o
The Null Hypothesis - H0: The random errors will be normally distributed The Alternative Hypothesis - H1: The random errors are not normally distributed Reject H0: when P-v
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whats mean by Double Exponential Smoothing
1 A penny is tossed 5 times. a. Find the chance that the 5th toss is a head b. Find the chance that the 5th toss is a head, given the first 4 are tails.
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Complete the multiple regression model using Y and your combined X variables. State the equation. Next, make sure that you evaluate overall model performance with the Anova table
Test the following claim. Identify the null hypothesis, alternative hypothesis, test statistic, critical value(s), conclusion about the null hypothesis, and final conclusion that
Advantages of Sampling Why should we settle on a sample instead of studying the entire population? Sampling has the following advantages over a census (study of the entire pop
1. For each of the following variables: major, graduate GPA, and height: a. Determine whether the variable is categorical or numerical. b. If the variable is numerical, deter
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