Question

10 | A) | What is the best regression to forecast salary? | ||||

10 | C) | Are all variables statistically significant? Did you drop any | ||||

Final | Math Pre req | Hours | Work experience | |||

94 | 92 | 5 | Y | |||

74 | 90 | 3 | Y | |||

74 | 87 | 4 | Y | |||

76 | 84 | 3 | N | |||

66 | 87 | 2 | N | |||

80 | 49 | 4 | Y | |||

74 | 42 | 3 | N | |||

71 | 61 | 4 | N | |||

84 | 81 | 5 | N | |||

76 | 67 | 5 | Y | |||

95 | 93 | 4 | N | |||

78 | 56 | 5 | N | |||

71 | 54 | 3 | Y | |||

82 | 96 | 2 | N | |||

65 | 50 | 3 | N | |||

77 | 86 | 2 | N | |||

78 | 88 | 2 | Y | |||

63 | 78 | 2 | Y | |||

76 | 55 | 5 | Y | |||

71 | 44 | 4 | Y | |||

70 | 80 | 1 | Y | |||

73 | 80 | 4 | Y | |||

62 | 41 | 2 | Y | |||

70 | 69 | 4 | N | |||

60 | 51 | 2 | N | |||

76 | 79 | 4 | Y | |||

70 | 54 | 2 | N | |||

55 | 53 | 1 | N | |||

77 | 58 | 5 | N | |||

81 | 97 | 2 | Y | |||

59 | 42 | 1 | N | |||

95 | 76 | 5 | N | |||

59 | 57 | 2 | Y | |||

64 | 57 | 2 | N | |||

61 | 80 | 2 | N | |||

74 | 65 | 3 | N | |||

75 | 87 | 3 | N | |||

76 | 42 | 4 | N | |||

75 | 67 | 3 | Y | |||

71 | 89 | 3 | N | |||

72 | 71 | 3 | N | |||

84 | 53 | 5 | N | |||

73 | 68 | 2 | Y | |||

83 | 83 | 4 | N | |||

57 | 54 | 1 | N | |||

79 | 88 | 4 | Y | |||

88 | 90 | 4 | N | |||

69 | 93 | 2 | N | |||

82 | 76 | 5 | N | |||

52 | 46 | 3 | Y | |||

71 | 61 | 2 | Y | |||

66 | 47 | 4 | N | |||

69 | 60 | 3 | N | |||

74 | 56 | 5 | N | |||

62 | 83 | 1 | Y | |||

62 | 41 | 2 | Y | |||

78 | 80 | 4 | Y | |||

66 | 43 | 2 | Y | |||

78 | 41 | 5 | Y | |||

63 | 64 | 2 | Y |

Answer #1

**Dear student, please comment in the case of any doubt
and I would love to clarify it. **

**A)**

**Linear regression** is the right regression
algorithm to forecast salaries.

In Supervised Machine Learning, Regression algorithms help us to build a model by which we can predict the values of a dependent variable from the values of one or more independent variables. For example, predicting future demand for a product based on previous demand.

**C)**

We know the fact that machine only understands numerical data, we do have numerical data for all the columns except work experience, we will convert it into numbers, we can take Y as 1 and N as 0 here and create the model.

All the variables are relevant here and will be included in the model creation.

Student Grades
Student
Test
Grade
1
76
62
2
84
90
3
79
68
4
88
84
5
76
58
6
66
79
7
75
73
8
94
93
9
66
65
10
92
86
11
80
53
12
87
83
13
86
49
14
63
72
15
92
87
16
75
89
17
69
81
18
92
94
19
79
78
20
60
71
21
68
84
22
71
74
23
61
74
24
68
54
25
76
97...

Use ? to approximate σ. Use a 5% level of significance.
Data:
69
62
75
66
68
57
61
84
61
77
62
71
68
69
79
76
87
78
73
89
81
73
64
65
73
69
57
79
78
80
79
81
73
74
84
83
82
85
86
77
72
79
59
64
65
82
64
70
83
89
69
73
84
76
79
81
80
74
77
66
68
77
79
78
77

Refer to the accompanying data set and construct a 95%
confidence interval estimate of the mean pulse rate of adult
females; then do the same for adult males. Compare the results.
Males Females
81
82
72
94
52
57
59
66
51
54
62
80
52
77
74
85
51
89
62
57
73
35
61
64
62
87
80
74
80
79
63
62
63
67
97
76
43
60
85
65
72
86
66
85
73
69
72 ...

Question 1: Table 1 shows the number of customers visited by a
salesman over an 80-week period. Table 1: Customers Visited Over an
80-Week Period 68 64 75 82 68 60 62 88 76 93 73 79 88 73 60 93 71
59 85 75 61 65 75 87 74 62 95 78 63 72 66 78 82 75 94 77 69 74 68
60 96 78 89 61 75 95 60 79 83 71 79 62 67 97 78...

Below represent scores on an exam, each entry one score for one
student
40
99
59
98
63
63
64
65
67
35
67
67
68
70
71
71
71
46
72
72
60
73
74
74
74
75
97
75
62
76
76
76
76
76
77
57
77
98
77
63
78
78
78
79
79
80
80
80
80
80
81
81
92
81
93
82
82
83
83
83
83
83
83
83
84
84
84...

Using the accompanying Student Grades data, construct a scatter
chart for midterm versus final exam grades and add a linear
trendline. What is the model? If a student scores 7878 on the
midterm, what would you predict her grade on the final exam to
be?
Student
Midterm
Final Exam
1
75
64
2
85
91
3
80
68
4
88
83
5
76
60
6
67
80
7
78
74
8
95
94
9
67
61
10
93
87
11...

The following scores represent a sample of final examination
grades for a statistics course
23 60 98 32 57 74 52 70 82 69 74 63 80 62 80 77 81 95 41 65 92
85 85 61 36 79 55 76 52 10 64 75 78 25 80 48 83 64 88 82 81 67 41
71 67 54 34 72 74 43 60 78 84 89 76 84 17 90 15 79
a) Compute the 20th percentile of...

TestScore
53
53
56
56
56
58
58
58
59
59
59
60
60
62
63
63
63
64
65
65
66
67
67
67
67
68
69
69
69
69
71
71
72
72
72
72
73
73
73
73
73
74
75
75
75
76
76
76
76
77
77
77
77
77
78
78
78
79
79
79
79
80
80
80
80
80
80
81
81
81
82
82
83
83
83
83
84
84
84...

Mid Score
Final Score
80
78
87
85
72
81
69
54
86
70
83
73
78
89
75
84
74
86
75
79
84
75
73
63
74
72
73
69
80
86
75
78
72
75
77
68
76
77
66
78
74
77
71
73
85
79
74
74
76
79
76
73
84
72
77
81
78
86
86
76
81
83
78
83
85
86
73
71
83
83
83
79
72
68
83
90...

#10. You are to determine if a new
online teaching model is better than the existing model, labelled
old. You administer random tests to a pre-selected group of
students first for material taught the old model and then under the
new model. The data is given in the Excel file and is labelled
problem # 10. Carry out an appropriate procedure in hypothesis
testing to determine if the new model is more effective for
learning.
new
old
78
4
86...

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