b) The raw material used in the production of a certain synthetic fibre is stored in a location without a humidity control. Measurements of the humidity (g/m ) in the storage location and the moisture content (%) of a sample of the raw material were taken over 10 days. The following table displays the recorded measurements. Humidity (g/m)) Moisture content (%) 46 12 53 15 29 7 36 10 39 11 52 14 55 16 32 8 57 18 54 14 The above data were analyzed using Minitab and the output is shown below. Regression Analysis: Humanity versus Moisture Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 9.47 3.22 2.94 0.019 Moisture 2.867 0.249 11.53 0.000 1.00 Model Summary R-sq R-sq(adj) R-sq(pred) 2.63629 W% 93.62% 90.54% Analysis of Variance Source DF Adj SS Adj MS F-Value P-Value Regression 924.500 924.500 133.02 0.000 Moisture 924.500 924.500 133.02 0.000 Error 55.600 6.950 Total 980.100 Assume that both the variables are normally distributed, answer the following questions. i) State the independent and dependent variables. (2 marks) ii) Calculate the Pearson Product Moment Correlation Coefficient of the above data and explain its meaning? Leave all calculated values to 4 decimal places. (5 marks) iii) Find the coefficient of determination and interpret the value. (2 marks) iv) How do you determine whether the above data set is suitable to be modelled using a Simple Linear Regression? Explain your answer clearly. (2 marks) v) Write down the linear regression equation of this study and interpret the value of the slope. (3 marks) vi) Is it possible to use the linear regression equation in (v) to estimate the humidity when the moisture content is 25%? Justify your answer. (2 marks) vii) Test whether the linear regression model is significant at 5% significance level. (4 marks)