The dataset below contains synthetic records of human heights and weights of 18 years old children. HEIGHT WEIGHT (Feet) (in kg) 5.48 51.36 5.96 62.04 5.78 69.56 5.69 64.70 5.65 65.59 5.73 56.05 5.82 64.31 5.83 62.03 а. Find the equation of the regression that model the relationship between the weight of mail and number of order using LINEAR EQUATION, EXPONENTIAL EQUATION, SIMPLE POWER EQUATION, and HYPERBOLIC| EQUATION. b. Compute for the correlation coefficient of each equation using PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT (PPMCC).

College Algebra
1st Edition
ISBN:9781938168383
Author:Jay Abramson
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Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
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The dataset below contains synthetic records of human heights and weights of 18 years old children.
HEIGHT
WEIGHT
(Feet)
(in kg)
5.48
51.36
5.96
62.04
5.78
69.56
5.69
64.70
5.65
65.59
5.73
56.05
5.82
64.31
5.83
62.03
а.
Find the equation of the regression that model the relationship between the weight of mail and number
of order using LINEAR EQUATION, EXPONENTIAL EQUATION, SIMPLE POWER EQUATION, and HYPERBOLIC|
EQUATION.
b. Compute for the correlation coefficient of each equation using PEARSON PRODUCT MOMENT
CORRELATION COEFFICIENT (PPMCC).
Transcribed Image Text:The dataset below contains synthetic records of human heights and weights of 18 years old children. HEIGHT WEIGHT (Feet) (in kg) 5.48 51.36 5.96 62.04 5.78 69.56 5.69 64.70 5.65 65.59 5.73 56.05 5.82 64.31 5.83 62.03 а. Find the equation of the regression that model the relationship between the weight of mail and number of order using LINEAR EQUATION, EXPONENTIAL EQUATION, SIMPLE POWER EQUATION, and HYPERBOLIC| EQUATION. b. Compute for the correlation coefficient of each equation using PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT (PPMCC).
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