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The scatter plot of SRES1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plot show that there many vertical structural breaks clearly visible. There are many outliers that can be seen and are obvious when analyzing these scatter plot. There is no leverage or influential points that are determining the slope of the line of best fit. There is no heteroscedasticity in this scatter graph which means there is constant variance. This scatter plot is very similar to the scatter plots conducted in the original regression which included the 17 outliers that I removed.
The scatter plot of SRES1 versus income demonstrates that there is a non-linear relationship that exists as points are randomly above or below zero and there are no vertical structural breaks. There is a cluster of data points clearly visible. There are outliers that can be seen and are obvious when analyzing the scatter plot. There is no leverage or influential points that are determining the slope of the line of best fit. There is no heteroscedasticity in this scatter graphs which means there is constant variance. This scatter plot is very similar to the scatter plots conducted in the original regression which included the 17 outliers that I removed.
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hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you
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