Root mean square error, so what we're going toĭo is is for every point, we're going to calculate the residual and then we're going to square it and then we're gonna add up the sum of those squared residuals, so we're gonna take the sum of the residuals, residuals squared and then we're going to divide that by the number of data Mean square deviation, sometimes abbreviated RMSD, sometimes it's called Now the way that we're going to measure how good a fit this regression line is to the data has several names, one name is the standardĭeviation of the residuals, another name is the root Regression line is by hand and typically you would not do it by hand, we have computers for that. More than four data points, the reason why I kept this to four is because we are actually This type of analysis, you would do it with far Things to keep in mind, normally when you're doing Is the actual regression line for these four data points and here is the equationįor that regression line. They got a one on the test and then we're going toįit a regression line and this blue regression line Studied and their score, so for example, this data point is someone who studied an hour and Going to plot for each person the amount that they So we are interested in studying the relationship between the amount that folks study for a testĪnd their score on a test, where the score is between zero and six and so what we're going toĭo is go look at the people who took the test, we're
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