A Clear and Present Danger to the Caribbean: Climate Change or Climate Alarmism? Reynold J. Stone Department of Food Production
Warming Trend
Percent of Days Tmax > 90 th Percentile
Wilks, D.S Statistical Methods in the Atmospheric Sciences. Academic Press, San Diego. It is not sufficient to blindly feed data to a computer regression package and uncritically accept the results. Some of the results can be misleading if the assumptions underlying the computations are not satisfied. Since the assumptions pertain to residuals, it is important to examine the residuals for consistency with the assumptions made about their behaviour.
Assumptions of OLS Regression Linearity Homoscedasticity Independence Normality Outliers
Anscombe, F.J Graphs in Statistical Analysis. American Statistician 27:
Residual Patterns
Residual Plot
Normal Plot
Percent Warm Days ( )
Percent Warm Days ( )
Diagnostic Checks Results ASSUMPTIONTESTRESULT LinearityHalf-Slope RatioViolated HomoscedascityMSE ratioViolated IndependenceDurbin-WatsonNot violated NormalityRyan-JoinerViolated OutliersLMS Procedure 1995, 1998
Percent Warm Days ( ) Excluding 1995, 1998
Conclusion #1 The claim of an increasing linear trend in the percent of warm days in the Caribbean during has no valid statistical basis, is erroneous and misleading.
Conclusion #2 Climate scientists must exercise greater care in their statistical analyses to avoid contributing to climate alarmism with erroneous and misleading conclusions.