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- https://stats.libretexts.org/Courses/Long_Beach_City_College/Book%3A_STAT_227_-_Introductory_Statistics/Text/12%3A_Linear_Regression_and_Correlation/12.06%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
- https://stats.libretexts.org/Courses/Marian_University/Applied_Statistics_for_Social_Science_(19-20)/09%3A_Linear_Regression_and_Correlation/9.6%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
- https://stats.libretexts.org/Courses/Lake_Tahoe_Community_College/MATH-201%3A_Elements_of_Statistics_and_Probability/12%3A_Linear_Regression_and_Correlation/12.06%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
- https://stats.libretexts.org/Courses/Los_Angeles_City_College/Introductory_Statistics/13%3A_Linear_Regression_and_Correlation/13.06%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
- https://stats.libretexts.org/Courses/Marian_University/Applied_Statistics_for_Social_Science/09%3A_Linear_Regression_and_Correlation/9.6%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
- https://stats.libretexts.org/Courses/Remixer_University/Username%3A_ckkidder08marianuniversityedu/Applied_Statistics_for_Social_Science_(19-20)/09%3A_Linear_Regression_and_Correlation/9.6%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
- https://stats.libretexts.org/Courses/El_Camino_College/Introductory_Statistics/12%3A_Linear_Regression_and_Correlation/12.06%3A_PredictionAfter determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process...After determining the presence of a strong correlation coefficient and calculating the line of best fit, you can use the least squares regression line to make predictions about your data. The process of predicting inside of the observed x values observed in the data is called interpolation. The process of predicting outside of the observed x-values observed in the data is called extrapolation.
