You may use excel to answer questions. Copy relative results (figures, tables, plots) generated while answering each question. Explain them if needed. 1. Reduce the noise effect of the following data set with respect to the given binning techniques. 2,2,3,3,13,15,16,16,19,20, 20, 21, 22, 22, 25, 25, 25, 25, 30, 33, 33, 33, 35, 35,35,35, 35, 35, 36, 40, 45, 46, 52, 70, 71, 77, 78, 80, 81, 81, 81 a. Use the equal depth of 3 and apply the "mean" (you should complete this section by the Excel) b. Use the equal depth of 3 and apply the "boundaries" (you should complete this section by the Excel) C. Use the equal width method with the total of 6 bins and apply "boundaries" ( you should complete this section by the Excel) (9marks) 2. Use the methods below to normalize the following group of data: 100, 150,200, 300, 400, 600, 1000, 1500, 2000 (a) min-max normalization by setting min = 0 and max = 1 (1 marks) (b) z-score normalization (1 marks) 3. List the major steps considering in data preprocessing to prepare data for data mining analysis (2 marks) 4. What is the range of Pearson test? Explain it. (2 marks) 6. How can we use correlation analysis (Pearson text) to reduce the number of decision variables? (input variables). (3marks) You may use excel to answer questions. Copy relative results (figures, tables, plots) generated while answering each question. Explain them if needed. 1. Reduce the noise effect of the following data set with respect to the given binning techniques. 2,2,3,3,13,15,16,16,19,20, 20, 21, 22, 22, 25, 25, 25, 25, 30, 33, 33, 33, 35, 35,35,35, 35, 35, 36, 40, 45, 46, 52, 70, 71, 77, 78, 80, 81, 81, 81 a. Use the equal depth of 3 and apply the "mean" (you should complete this section by the Excel) b. Use the equal depth of 3 and apply the "boundaries" (you should complete this section by the Excel) C. Use the equal width method with the total of 6 bins and apply "boundaries" ( you should complete this section by the Excel) (9marks) 2. Use the methods below to normalize the following group of data: 100, 150,200, 300, 400, 600, 1000, 1500, 2000 (a) min-max normalization by setting min = 0 and max = 1 (1 marks) (b) z-score normalization (1 marks) 3. List the major steps considering in data preprocessing to prepare data for data mining analysis (2 marks) 4. What is the range of Pearson test? Explain it. (2 marks) 6. How can we use correlation analysis (Pearson text) to reduce the number of decision variables? (input variables). (3marks)