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In this activity, students will draw a scatter plot and a line. They will investigate the method of least squares by finding the residuals and the sum of the squares of the residuals. They will then test their line using the built-in linear regression model.
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In this activity, students will assess the strength of a linear relationship using a residual plot. They will also calculate the correlation coefficient and coefficient of determination to assess the data set. Students will then learn to transform one or two variables in the relationship to create a linear relationship.
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In this activity, students will draw a scatter plot and a line. They will investigate the method of least squares by finding the residuals and the sum of the squares of the residuals. They will then test their line using the built-in linear regression model.
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In this activity, students will assess the strength of a linear relationship using a residual plot. They will also calculate the correlation coefficient and coefficient of determination to assess the data set. Students will then learn to transform one or two variables in the relationship to create a linear relationship.
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In this activity, students will collect height and wingspan measurements and plot the data. They will then determine a line of best fit using a movable line. Through teacher-led discussion, students will learn the properties of a line of best fit.
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In this activity, students will collect height and wingspan measurements and plot the data. They will then determine a line of best fit using a movable line. Through teacher-led discussion, students will learn the properties of a line of best fit.
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In this activity, students will determine, by examining a graph, if a data set has a positive or negative correlation coefficient. Then, they will find the linear regression equation and calculate the correlation coefficient. They will use this line to predict the value of y for a given x and vice-versa. Finally, students will investigate the effect of outliers and influential points on the regression equation and correlation coefficient.
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In this activity, students will determine, by examining a graph, if a data set has a positive or negative correlation coefficient. Then, they will find the linear regression equation and calculate the correlation coefficient. They will use this line to predict the value of y for a given x and vice-versa. Finally, students will investigate the effect of outliers and influential points on the regression equation and correlation coefficient.
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You can search this electronic textbook for statistics topics including ANOVA, linear regression models, the effects of outliers, confidence intervals, etc. Gives explanations and discusses the topics.
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Site contains several calculators evaluating several values in statistics including probabilties, t-test, ANOVA tests, least squares regression lines, etc.
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