aperatures since 1902 in Waco, Texas and available on CANVAS as Tempsrain 015.JM
ID: 3158725 • Letter: A
Question
aperatures since 1902 in Waco, Texas and available on CANVAS as Tempsrain 015.JMP and Tem Rain g data was obtained from the U.S. Meteorological Service on annual Year5 JMP and Tempsrain Lags 2015.xlsx or Tempsrain lags 2015.xls: Year Ave5 2015 53.74658 2014 30.09 Lag2 201 53.74 67.32877 2013 37.89 2012 32.34 2011 27.63 2010 2009 37.53 0.09 65.83068 67.32877 37.89 66.18658 65.83068 67.32877 32.34 69.03 66.18658 65.83068 67.32877 27.63 69.56 34 69 67.9 67.43 69.56 69.03 66.18658 68.02132 69.56 69.03 68.184 40.1 67.43 69.56 69.03 66.18658 65.83068 67.60745 67.43 2008 33.54 2007 48.04 67 66.7 67.9 67 67.9 67.43 69.56 67.718 Year is the year of the observed Temps or Rain which are annual average temperatures and total rainfall, respectively. Lagl through Lag4 are the Temps "lagged" by years with Ave5 the average of Temps, Lagl to Lag4 used to average out the year to year variability. What is the model? Give a measure of how good the model is as a proportion of the total variability in the model. (30) Is there a significant simple linear model for Ave5 by Year from 1902 to 2010? What is the model? How good is the model? Is the slope equal to -0.01? That would be the equivalent of 1°F in 100 years. (40) Looking at Ave5 there was a minimum at or near 1975. Is there a significant linear model for Ave5 from 1975 to present? Is the slope greater than zero? Comment on this versus part B. (40) A. Is there a significant simple linear model for Temps by Year from 1902 to 2014? B. C. Mandible measurements have heen made on 5 varieties of canines: Modern dogsExplanation / Answer
The model is not good at all. First of all, the data points are all over the place. The line going through the data is not anywhere near of the maximum points. the main purpose of fitting a model is to explain the data points as good as you can. but here the model is not fulfilling its purpose. we can explain it analytically also. if we check adjusted R2, its value is 0.016 thats mean 1.6% which is next to 0. so, the model explains only 1.6% of the total variability of the data. If we consider the significance of the coefficients of the model, we can see that the coefficient of X is not significant at 5% level of signiificance, considering its p-value (0.09). So, there is no effect of the independent variable at the model at all. So overall we can say that this model is of no use.
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