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POTEAU OKLAHOMA WINTER WEATHER RECORD BREAKING FORECASTS DEC. 2021 - MARCH 2022 STATISTICS.

No other model in the world through a book published is that accurate. This book has broken all forecast records from government and commercial entities worldwide when it comes to wind and precipitation for a localized city. Wind and precipitation statistics for the book POTEAU OKLAHOMA WINTER WEATHER FORECASTS (lulu.com) December 21, 2021 - March 21, 2022. The model book was 78% accurate in wind and 73% accurate in precipitation throughout the period of day-by-day forecasts. The National Weather Service in Chicago Illinois in October of 2022 said that those statistical numbers were impressive for such a long-range forecast in advance and that no way they or any other weather entity could complete such a task. These forecasts were written in a book and published through LuLu on August 7, 2021, and are 4 to 7 months in advance day-to-day.


View(windprecip)

> summary(windprecip)

   Wind    Precipitation  

 Min.  : 0.00  Min.  : 0.00  

 1st Qu.:100.00  1st Qu.: 0.00  

 Median :100.00  Median :100.00  

 Mean  : 79.52  Mean  : 73.49  

 3rd Qu.:100.00  3rd Qu.:100.00  

 Max.  :100.00  Max.  :100.00  

> plot(windprecip)

> cor(windprecip)

          Wind Precipitation

Wind     1.00000000  0.03341267

Precipitation 0.03341267  1.00000000

> windprecip.lm <- lm(wind ~ precipitation, data = windprecip)

Error in eval(predvars, data, env) : object 'wind' not found

> windprecip.lm <-(Wind ~ Precipitation, data = windprecip)

Error: unexpected ',' in "windprecip.lm <-(Wind ~ Precipitation,"

> windprecip.lm <- lm(Wind ~ Precipitation, data = windprecip)

> summary(windprecip)

   Wind    Precipitation  

 Min.  : 0.00  Min.  : 0.00  

 1st Qu.:100.00  1st Qu.: 0.00  

 Median :100.00  Median :100.00  

 Mean  : 79.52  Mean  : 73.49  

 3rd Qu.:100.00  3rd Qu.:100.00  

 Max.  :100.00  Max.  :100.00  

> windprecip.lm <- lm(Wind ~ Precipitation, data = windprecip)

> summary(windprecip.lm)


Call:

lm(formula = Wind ~ Precipitation, data = windprecip)


Residuals:

  Min   1Q Median   3Q  Max 

-80.33 19.67 19.67 19.67 22.73 


Coefficients:

       Estimate Std. Error t value Pr(>|t|)   

(Intercept)  77.27273  8.70484  8.877 1.39e-13 ***

Precipitation 0.03055  0.10154  0.301  0.764   

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


Residual standard error: 40.83 on 81 degrees of freedom

Multiple R-squared: 0.001116, Adjusted R-squared: -0.01122 

F-statistic: 0.09053 on 1 and 81 DF, p-value: 0.7643