PYTHON

coffeetemp.txt

0.0 83.0 1.0 77.7 2.0 75.1 3.0 73.0 4.0 71.1 5.0 69.4 6.0 67.8 7.0 66.4 8.0 64.7 9.0 63.4 10.0 62.1 11.0 61.0 12.0 59.9 13.0 58.7 14.0 57.8 15.0 56.6

(a) The file coffeeCooling.txt alongside, holds the time, Temp data for coffee cooling. Create a program that reads the data from the file and using matplotlib.pyplot To scatter-plot the data. Use the pyplot func- tions xlabel( ), ylabel( ) to label the axes approriately. (b) A model of coffee cooling in a room at To = 22C is: AT = Tn+1-Tn = -k(In-To). Use the function scipy.stats.linregress(x,y) (usage: slope, intercept, r_value, p-value, std_err = stats.linregress(x,y)), to make a fit of the coffee data given above. Make a plot of the regression line fit, superposed on a scatter plot of ATn v/s Tn To. (a) The file coffeeCooling.txt alongside, holds the time, Temp data for coffee cooling. Create a program that reads the data from the file and using matplotlib.pyplot To scatter-plot the data. Use the pyplot func- tions xlabel( ), ylabel( ) to label the axes approriately. (b) A model of coffee cooling in a room at To = 22C is: AT = Tn+1-Tn = -k(In-To). Use the function scipy.stats.linregress(x,y) (usage: slope, intercept, r_value, p-value, std_err = stats.linregress(x,y)), to make a fit of the coffee data given above. Make a plot of the regression line fit, superposed on a scatter plot of ATn v/s Tn To