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Construction linear regression equation.

Refer to data set and use the weights of discarded plastic and the corresponding household sizes. Find out the best predicted household size given that household discards 5.00 lb of plastic.

 

HHSIZE

METAL

PAPER

PLAS

GLASS

FOOD

YARD

TEXT

OTHER

TOTAL

2

1.09

2.41

0.27

0.86

1.04

0.38

0.05

4.66

10.76

3

1.04

7.57

1.41

3.46

3.68

0

0.46

2.34

19.96

3

2.57

9.55

2.19

4.52

4.43

0.24

0.5

3.6

27.6

6

3.02

8.82

2.83

4.92

2.98

0.63

2.26

12.65

38.11

4

1.5

8.72

2.19

6.31

6.3

0.15

0.55

2.18

27.9

2

2.1

6.96

1.81

2.49

1.46

4.58

0.36

2.14

21.9

1

1.93

6.83

0.85

0.51

8.82

0.07

0.6

2.22

21.83

5

3.57

11.42

3.05

5.81

9.62

4.76

0.21

10.83

49.27

6

2.32

16.08

3.42

1.96

4.41

0.13

0.81

4.14

33.27

4

1.89

6.38

2.1

17.67

2.73

3.86

0.66

0.25

35.54

4

3.26

13.05

2.93

3.21

9.31

0.7

0.37

11.61

44.44

7

3.99

11.36

2.44

4.94

3.59

13.45

4.25

1.15

45.17

3

2.04

15.09

2.17

3.1

5.36

0.74

0.42

4.15

33.07

5

0.99

2.8

1.41

1.39

1.47

0.82

0.44

1.03

10.35

6

2.96

6.44

2

5.21

7.06

6.14

0.2

14.43

44.44

2

1.5

5.86

0.93

2.03

2.52

1.37

0.27

9.65

24.13

4

2.43

11.08

2.97

1.74

1.75

14.7

0.39

2.54

37.6

4

2.97

12.43

2.04

3.99

5.64

0.22

2.47

9.2

38.96

3

1.42

6.05

0.65

6.26

1.93

0

0.86

0

17.17

3

3.6

13.61

2.13

3.52

6.46

0

0.96

1.32

31.6

2

4.48

6.98

0.63

2.01

6.72

2

0.11

0.18

23.11

2

1.36

14.33

1.53

2.21

5.76

0.58

0.17

1.62

27.56

4

2.11

13.31

4.69

0.25

9.72

0.02

0.46

0.4

30.96

1

0.41

3.27

0.15

0.09

0.16

0

0

0

4.08

4

2.02

6.67

1.45

6.85

5.52

0

0.68

0.03

23.22

6

3.27

17.65

2.68

2.33

11.92

0.83

0.28

4.03

42.99

11

4.95

12.73

3.53

5.45

4.68

0

0.67

19.89

51.9

3

1

9.83

1.49

2.04

4.76

0.42

0.54

0.12

20.2

4

1.55

16.39

2.31

4.98

7.85

2.04

0.2

1.48

36.8

3

1.41

6.33

0.92

3.54

2.9

3.85

0.03

0.04

19.02

2

1.05

9.19

0.89

1.06

2.87

0.33

0.01

0.03

15.43

2

1.31

9.41

0.8

2.7

5.09

0.64

0.05

0.71

20.71

2

2.5

9.45

0.72

1.14

3.17

0

0.02

0.01

17.01

4

2.35

12.32

2.66

12.24

2.4

7.87

4.73

0.78

45.35

6

3.69

20.12

4.37

5.67

13.2

0

1.15

1.17

49.37

2

3.61

7.72

0.92

2.43

2.07

0.68

0.63

0

18.06

2

1.49

6.16

1.4

4.02

4

0.3

0.04

0

17.41

2

1.36

7.98

1.45

6.45

4.27

0.02

0.12

2.02

23.67

2

1.73

9.64

1.68

1.89

1.87

0.01

1.73

0.58

19.13

2

0.94

8.08

1.53

1.78

8.13

0.36

0.12

0.05

20.99

3

1.33

10.99

1.44

2.93

3.51

0

0.39

0.59

21.18

3

2.62

13.11

1.44

1.82

4.21

4.73

0.64

0.49

29.06

2

1.25

3.26

1.36

2.89

3.34

2.69

0

0.16

14.95

2

0.26

1.65

0.38

0.99

0.77

0.34

0.04

0

4.43

3

4.41

10

1.74

1.93

1.14

0.92

0.08

4.6

24.82

6

3.22

8.96

2.35

3.61

1.45

0

0.09

1.12

20.8

4

1.86

9.46

2.3

2.53

6.54

0

0.65

2.45

25.79

4

1.76

5.88

1.14

3.76

0.92

1.12

0

0.04

14.62

3

2.83

8.26

2.88

1.32

5.14

5.6

0.35

2.03

28.41

3

2.74

12.45

2.13

2.64

4.59

1.07

0.41

1.14

27.17

10

4.63

10.58

5.28

12.33

2.94

0.12

2.94

15.65

54.47

3

1.7

5.87

1.48

1.79

1.42

0

0.27

0.59

13.12

6

3.29

8.78

3.36

3.99

10.44

0.9

1.71

13.3

45.77

5

1.22

11.03

2.83

4.44

3

4.3

1.95

6.02

34.79

4

3.2

12.29

2.87

9.25

5.91

1.32

1.87

0.55

37.26

7

3.09

20.58

2.96

4.02

16.81

0.47

1.52

2.13

51.58

5

2.58

12.56

1.61

1.38

5.01

0

0.21

1.46

24.81

4

1.67

9.92

1.58

1.59

9.96

0.13

0.2

1.13

26.18

2

0.85

3.45

1.15

0.85

3.89

0

0.02

1.04

11.25

4

1.52

9.09

1.28

8.87

4.83

0

0.95

1.61

28.15

2

1.37

3.69

0.58

3.64

1.78

0.08

0

0

11.14

2

1.32

2.61

0.74

3.03

3.37

0.17

0

0.46

11.7

 

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