1.2 Question 2 Suppose we want to investigate the relationship between money invested in newspaper advertisement and product sales. Data has been collected and is provided in the 'sales.cav'. Note that the data is in thousands of dollars. All, and only, relevant R code and output must be submitted with this question. 1. Calculate the correlation between the two variables. 2. Draw a scatterplot of the data. 3. Does a linear regression model seem appropriate for these data? Briefly justify. 4. Define the simple linear regression model, where sales is the response variable. Be sure to clearly define any variables you introduce. 5. Give the least squares regression line for the model in (4). 6. Using correlation, perform a hypothesis test to determine whether sales and dollars spent advertising in newspapers are linearly related. Be sure to clearly show all of the steps the hypothesis test. 1.3 Question 3 Please find a dataset by yourself that satisfies SLR model and use R for regression testing to give the model results.(Hint: You can follow the steps shows in Question 2)A B C D E F G H I J K L newspaper sales 83. 04 26. 52 54. 12 12. 48 83. 16 11. 16 70. 2 22. 2 DO SOUT AWN 70. 08 15. 48 90 8. 64 28. 2 14. 16 13. 92 15. 84 10 1. 2 5. 76 11 25. 44 12. 72 12 29. 04 10. 32 13 4. 8 20. 88 14 79. 08 11. 04 15 8. 64 11. 64 16 55. 2 22. 8 17 63. 48 26. 88 18 136. 8 15 19 66. 96 29. 28 20 21. 96 13. 56 21 22. 92 17. 52 22 64. 08 21. 6 23 28. 2 15 24 59. 52 6. 72 25 31. 44 18. 6 26 21. 96 11. 64 27 23. 4 14. 4 28 15. 12 18 29 27. 48 19. 08 30 27. 48 22. 68 31 48. 96 12. 6 32 51. 84 25. 68 33 46. 32 14. 28 34 36 11. 52 35 0. 36 20. 88 36 8. 88 11. 4 37 10. 2 15. 36 38 30. 48 39 54. 84 17. 64 40 42. 12 12. 12 41 38. 4 25. R > >1 sales +A B C D E F G H I J K L 42 37. 92 19. 92 43 46. 44 20. 52 44 2. 16 24. 84 45 31. 68 15. 48 46 51. 96 10. 2 47 37. 8 17. 88 48 42. 84 12. 72 49 22. 2 27. 84 50 59. 88 17. 76 51 44. 16 11. 64 52 41. 52 13. 68 53 4. 32 12. 84 54 47. 52 27. 12 55 70. 44 25. 44 56 19. 08 24. 24 57 72 28. 44 58 49. 68 6. 6 59 19. 92 15. 84 60 45. 24 28. 56 61 11. 16 22. 08 62 25. 68 9. 72 63 65. 64 29. 04 64 32. 76 18. 84 65 10. 08 16. 8 66 34. 68 21. 6 67 1 . 08 11. 16 68 2. 64 11. 4 69 12. 24 16. 08 70 13. 2 22. 68 71 32. 64 26. 76 72 46. 44 21. 96 73 38. 04 14. 88 74 23. 16 10. 56 75 37. 56 13. 2 76 15. 72 20. 4 77 107. 28 10. 44 78 24. 84 B. 28 79 17. 04 17. 04 80 11. 28 6. 36 81 27. 72 13. 2 82 26. 76 14. 16 > sales +A B C D E F G H I J K L 83 44. 28 14. 76 84 39 13. 56 85 42. 72 16. 32 86 40. 56 26. 04 87 78. 84 18. 24 88 19. 2 14. 4 89 75. 84 19. 2 90 88. 08 15. 48 91 61. 68 20. 04 92 11. 16 13. 44 93 39. 6 3. 76 94 70. 8 23. 28 95 86. 76 26. 64 96 13. 08 13. 8 97 63. 48 20. 28 98 7. 08 14. 04 99 26. 4 18. 6 100 61. 44 30. 48 101 55. 08 20. 64 102 59. 76 14. 04 103 121. 08 28. 56 104 25. 68 17. 76 105 21. 48 17. 64 106 6. 36 24. 84 107 70. 8 23. 04 108 35. 64 8. 64 109 27. 84 10. 44 110 30. 72 6. 36 111 6. 6 23. 76 112 67. 8 16. 08 113 27. 84 26. 16 114 2. 88 16. 92 115 12. 84 19. 08 116 41. 4 17. 52 117 63. 24 15. 12 118 30. 72 14. 64 119 17. 76 11. 28 120 95. 04 19. 08 121 26. 76 7. 92 122 55. 44 18. 6 123 60. 48 R. 4 >1 sales +A B C D E F G H I J K L 124 18. 72 13. 92 125 14. 88 18. 24 126 89. 04 23. 64 127 31. 08 12. 72 128 60. 72 7. 92 129 11. 04 10. 56 130 3. 84 29. 64 131 51. 72 11. 64 132 10. 44 1. 92 133 51. 6 15. 24 134 2. 52 6. 84 135 54. 12 23. 52 136 78. 72 12. 96 137 10. 2 13. 92 138 11. 16 11. 4 139 71. 64 24. 96 140 24. 6 11. 52 141 2. 04 24. 84 142 15. 48 13. 08 143 90. 72 23. 04 144 45. 48 24. 12 145 41. 28 12. 48 146 46. 68 13. 68 147 10. 8 12. 36 148 10. 44 15. 84 149 53. 16 30. 48 150 14. 28 13. 08 151 24. 72 12. 12 152 44. 4 19. 32 153 58. 44 13. 92 154 17. 04 19. 92 155 45. 24 22. 8 156 11. 4 18. 72 157 6. 84 3. 84 158 60. 6 18. 36 159 29. 16 12. 12 160 54. 24 8. 76 161 41. 52 15. 48 162 36. 84 17. 28 163 59. 16 15. 96 164 30. 72 17. RR >1 sales +