Using Matlab Background: Work through Matlab Exercise 2 (posted with this assignment). Steps #8 and #9 pertain to th...
Background: Work through Matlab Exercise 2 (posted with this assignment). Steps #8 and #9 pertain to this problem. Consider the following sample of ordered pairs (x. y) where y = the purity of oxygen produced in a chemical distillation process, and x the percentage of hydrocarbons that are present in the main condenser of the distillation unit Hydrocarbon Level; x (in %) Purity y (in %) Observation Hydrocarbon Observation Purity Level; x (in %) y (in % ) Number Number 1 0.99 90.01 11 1.19 93.65 2 1.02 89.05 12 1.15 92.52 3 1.15 91.43 13 0.98 90.56 4 1.29 93.74 14 1.01 89.54 96.73 5 1.46 15 1.11 89.85 6 1,36 1.2 90.39 94.45 16 7 0.87 87.59 17 1.26 93.25 8 1.23 91.77 18 1.32 93.41 1.55 99.42 19 1.43 94.98 10 1.4 93.65 20 0.95 87.33 Enter above data either as a single 20x2 matrix or as two 20x1 vectors. Be sure to preserve the ordering of the pairs. 0. Create a scatterplot of this data. Label both the x and y axis' and title the graph "scatterplot" Labels can be added on the graph itself by choosing "Insert" drop down menu. a. Determine the correlation coefficient. b. The corrcoef(x.y) command produces a 2x2 matrix with 1's down the principle diagonal Cell 1, provides the correlation of x with itself and cell 2,2 is the correlation of y with itself (both of which are 1). Cell 2,1 provides the correlation between x and y, cell 1,2 provides the correlation between y and x (both, of course would be the same) Find the equation of the least square regression line, 9 bo + bx and determine the p-value of the slope term b. To generate the line and obtain the p-value you should use the fitlm command (refer to Matlab exercise 2). Using the 5 % Significance Level, if the p-value < .05, then the linear model is statistically significant. You can also display the regression equation on your scatterplot by selecting "Tools" drop down menu, select "basic fitting", linear d. If your regression model is statistically significant then use it to estimate Oxygen purity (in %) when the hydrocarbon level in the main condenser of the distillation unit is 1%. e.
Background: Work through Matlab Exercise 2 (posted with this assignment). Steps #8 and #9 pertain to this problem. Consider the following sample of ordered pairs (x. y) where y = the purity of oxygen produced in a chemical distillation process, and x the percentage of hydrocarbons that are present in the main condenser of the distillation unit Hydrocarbon Level; x (in %) Purity y (in %) Observation Hydrocarbon Observation Purity Level; x (in %) y (in % ) Number Number 1 0.99 90.01 11 1.19 93.65 2 1.02 89.05 12 1.15 92.52 3 1.15 91.43 13 0.98 90.56 4 1.29 93.74 14 1.01 89.54 96.73 5 1.46 15 1.11 89.85 6 1,36 1.2 90.39 94.45 16 7 0.87 87.59 17 1.26 93.25 8 1.23 91.77 18 1.32 93.41 1.55 99.42 19 1.43 94.98 10 1.4 93.65 20 0.95 87.33 Enter above data either as a single 20x2 matrix or as two 20x1 vectors. Be sure to preserve the ordering of the pairs. 0. Create a scatterplot of this data. Label both the x and y axis' and title the graph "scatterplot" Labels can be added on the graph itself by choosing "Insert" drop down menu. a. Determine the correlation coefficient. b. The corrcoef(x.y) command produces a 2x2 matrix with 1's down the principle diagonal Cell 1, provides the correlation of x with itself and cell 2,2 is the correlation of y with itself (both of which are 1). Cell 2,1 provides the correlation between x and y, cell 1,2 provides the correlation between y and x (both, of course would be the same) Find the equation of the least square regression line, 9 bo + bx and determine the p-value of the slope term b. To generate the line and obtain the p-value you should use the fitlm command (refer to Matlab exercise 2). Using the 5 % Significance Level, if the p-value