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Canonical correlation analysis (CC) allows the investigation of the relationship between two ,sets of variables. For example, a sociologist may want to investigate the Relationship between two predictors of social mobility based on interviews, with actual subsequent social nlobility as measured by four different indicators. A medical researcher may want to study the relationship of various risk factors to the development of a group of symptoms. In all of these cases, the researcher is interested in the relationship betweet; ' two, sets of variables, and Canonical Correlation would be the appropriate method of analysis. . Canonical Correlation combines the dependent variables to find pairs, of new variables called canonical variables, CV, 'one for each data table having the highest . correlation. However, the CV's, even when highly correlated, do not necessarily explain a large portion of the variance of the original tables. This makes the interpretation of the CV sometimes difficult, but CC is nonetheless an important theoretical tool because most multivariate techniques can be interpreted as a special case of CC.
We are interested in assessing the effects of temperature (low, medium, and high) and technical configuration on the amount of waste output for a manufacturing plant. Suppose that
Regression Lines It has already been discussed that there are two regression lines and they show mutual relationship between two variable . The regression line Yon X gives th
First we look at these charts assuming that we know both the mean and the standard deviation of the process, that is μ and σ . These values represent the acceptable values (bench
Testing of Hypothesis One objective of sampling theory is Hypothesis Testing. Hypothesis testing begins by making an assumption about the population parameter. Then we gather
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what are characteristics of a population for which it would be appropiate to use mean/median/mode
history of north west corner method
As we stated above, we start factor analysis with principal component analysis, but we quickly diverge as we apply the a priori knowledge we brought to the problem. This knowled
An approximation to the error of a Riemannian sum: where V g (a; b) is the total variation of g on [a, b] dened by the sup over all partitions on [a, b], including (a; b
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
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