My problem is that the regression lines, when plotted, are quite different from what I would have expected from the scatterplot.
12.
:* \ alpha _ { ( Q ) } is estimated as the slope of the regression line for versus where:
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For example, when estimating the median, it uses the sample median; to estimate the population regression line, it uses the sample regression line.
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The two regression lines appear to be very similar ( and this is not unusual in a data set of this size ).
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For example, when estimating the median, it uses the sample median; to estimate the population regression line, it uses the sample regression line.
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Galton invented the use of the regression line and for the choice of r ( for reversion or regression ) to represent the correlation coefficient.
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This shows that is the slope of the regression line of the standardized data points ( and that this line passes through the origin ).
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In a linear regression line example, the original data can be plotted, and a best fit line is a synthesizer created from the original data.
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These results suggest that rather than a single regression line for the data set, a segmental regression may be a better model for genuinely random distributions.
20.
If brain weight is plotted against body weight for primates, the regression line of the sample points can indicate the brain power of a primate species.
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