Project #94705 - Regression peek

    1. Create a scatterplot of the data you signed up for. Try to label the axes within the graph, but if that turns out to be a pain in the neck, just explain in the body of your post what each axis represents. (Be specific! Use units!) 

    2. On top of your scatterplot, graph ONE regression curve of choice. It may or may not be a good fit -- doesn't matter! Explain what type of equation (linear, quadratic, logarithmic, etc.) you're using to model the data and show the equation. (Feel free to round coefficients as you see fit.) 

    3. Discuss what the R2 value is for the regression you just created, and whether or not it "agrees" with your assessment as to whether or not this is a good model. Use the fill-in-the-blank sentence from the project instructions to start your analysis of the R2 value.

In summary, you need to embed or attach ONE graph (a scatter plot with a regression curve over it), show the equation of the model and explain what type of model it is, and talk about the R-squared value

Data for part one:

Male Waist (in cm) vs BMI (in kg/m2 ) (Data from National Center for Health Statistics)

Waist      BMI

81.4,       20.14

74.8        19.62

84.1,       22.26

95.5,       29.04

90.1,       22.14

69.8,       20.48

137.8,     38.45

94.4,       23.80

74.2,       20.82

69.9,       17.27

95.2,       26.46

117.5,     34.45

77.0,       20.37

90.5,       25.61

122.0,     33.89

104.0,     28.17

104.1,    33.21

76.4,      20.34

98.6,      29.45

89.7,      26.33

102.1,    29.71

104.6,    29.46

77.6,      20.52

87.5,      21.65

69.1,     17.84

83.4,     26.60

96.1,     28.21

97.2,     27.96

122.4,   36.75

81.5,     21.79

97.5,      32.38

106.7,   33.27

109.6,   30.95

91.8,     26.45

96.7,     27.86

86.6,     27.08

118.1,   32.28

81.5,     25.00

92.1,    26.13

103.3,  29.83 http://www.alcula.com/calculators/statistics/scatter-plot/scatter-plot-image.php?n=0

 

 

 

 

Subject Mathematics
Due By (Pacific Time) 11/22/2015 02:00 pm
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