obtain the data sample in R programming, use direct X-Y variable plots and residuals vs. fitted value plots implemented in R, as well as perhaps other types of plots and/or regression diagnostic tests and/or goodness-of-fit measures and the like, to identify an appropriate linear regression model (possibly requiring transformations of the variables, for example)that seems reasonably consistent with the data. Please explain why you believe your model may be a valid one.

Y X

1 0.31516717 10

2 0.29840661 11

3 0.26440082 12

4 0.25592625 13

5 0.23242195 14

6 0.25393143 15

7 0.20726179 16

8 0.21646884 17

9 0.21283162 18

10 0.20793431 19

11 0.18557348 20

12 0.19770221 21

13 0.18743669 22

14 0.18596253 23

15 0.16609693 24

16 0.18225363 25

17 0.17240596 26

18 0.18918715 27

19 0.15970456 28

20 0.16644 29

21 0.14981437 30

22 0.15527959 31

23 0.15500805 32

24 0.14667555 33

25 0.15203673 34

26 0.13548623 35

27 0.14317628 36

28 0.14503285 37

29 0.13834512 38

30 0.13663367 39

31 0.13963679 40

32 0.13548225 41

33 0.12915889 42

34 0.1303814 43

35 0.12921471 44

36 0.1309655 45

37 0.1251231 46

38 0.12720316 47

39 0.12237968 48

40 0.1217552 49

41 0.12284425 50

42 0.12484094 51

43 0.12000439 52

44 0.11603564 53

45 0.11193979 54

46 0.11508095 55

47 0.11575496 56

48 0.1153174 57

49 0.11350509 58

50 0.11151227 59

51 0.10605045 60

52 0.10944887 61

53 0.10907688 62

54 0.10641832 63

55 0.10596407 64

56 0.10669879 65

57 0.10345642 66

58 0.10239457 67

59 0.09875031 68

60 0.09954197 69

61 0.10017769 70

62 0.10172107 71

63 0.09840623 72

64 0.09784649 73

65 0.09848659 74

66 0.09814287 75

67 0.09657689 76

68 0.09355607 77

69 0.09418504 78

70 0.09228569 79

71 0.09329148 80

72 0.09550943 81

73 0.09336515 82

74 0.0923631 83

75 0.09081336 84

76 0.09092301 85

77 0.08840948 86

78 0.08849986 87

79 0.08996394 88

80 0.08839808 89

81 0.08771186 90

82 0.08842171 91

83 0.08663598 92

84 0.08501201 93

85 0.08695408 94

86 0.08509321 95

87 0.08406209 96

88 0.08504328 97

89 0.08541706 98

90 0.08266703 99

91 0.08328653 100