Plot(age, glucose.level, fill=“blue”, fit=“lm”, data=df) [Interactive chart from the Plotly R package (Sievert, 2020)]

Suggestions or enter: style(suggest=FALSE) XY(age, glucose.level, enhance=TRUE) # many options XY(age, glucose.level, out_cut=.10) # label top 10% from center as outliers

Pearson’s product-moment correlation

Number of paired values with neither missing, n = 5110 Sample Correlation of age and glucose.level: r = 0.238

Hypothesis Test of 0 Correlation: t = 17.527, df = 5108, p-value = 0.000 95% Confidence Interval for Correlation: 0.212 to 0.264

Line: b0 = 85.530 b1 = 0.477 Linear Model MSE = 1,934.658 Rsq = 0.057

Plot(age, glucose.level, fill=“red”, fit=“lm”, data=df) [Interactive chart from the Plotly R package (Sievert, 2020)]

Suggestions or enter: style(suggest=FALSE) XY(age, glucose.level, enhance=TRUE) # many options XY(age, glucose.level, out_cut=.10) # label top 10% from center as outliers

Pearson’s product-moment correlation

Number of paired values with neither missing, n = 5110 Sample Correlation of age and glucose.level: r = 0.238

Hypothesis Test of 0 Correlation: t = 17.527, df = 5108, p-value = 0.000 95% Confidence Interval for Correlation: 0.212 to 0.264

Line: b0 = 85.530 b1 = 0.477 Linear Model MSE = 1,934.658 Rsq = 0.057

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