Co-variability between Gender and Height

Call:
lm(formula = log(mini_data_set$Weight) ~ mini_data_set$Height)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.0982 -0.1451 -0.0132  0.1308  1.2417 

Coefficients:
                      Estimate Std. Error t value Pr(>|t|)    
(Intercept)          6.9985893  0.0353172  198.16   <2e-16 ***
mini_data_set$Height 0.0116506  0.0002075   56.16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.2099 on 9108 degrees of freedom
Multiple R-squared:  0.2572,    Adjusted R-squared:  0.2571 
F-statistic:  3154 on 1 and 9108 DF,  p-value: < 2.2e-16

Note the R-squared value: ~25 % of the variability in Weight can be attributed to the variability in Height. What attribution can be made to Gender?

• The app allows users to choose between displaying the distibution of Weight (Data obtained from the BRFSS Dataset) https://www.cdc.gov/brfss/annual_data/annual_2017.html through the framing reference of:

  • Gender
  • Aerobic Excercise - whether a survey respondant met the aerobic activitiy requirements or not per BRFSS research guidelines (see X_PAINDX1 in dataset codebook https://www.cdc.gov/brfss/annual_data/2017/pdf/codebook17_llcp-v2-508.pdf

• The app then invites the user to click a button to perform a regression analysis on Weight v. their chosen factor variable after controlling for Height.

• Apart from satisfying the requirements of the submission, the objective to the app is to demonstrate the co-variability between Gender and Height when considering variability in Weight among humans. Why not check it out?

The app can be found here https://gormonjee.shinyapps.io/Fun_with_weight/

The BRFSS dataset can be found here https://www.cdc.gov/brfss/annual_data/annual_2017.html

The github repo for the entire project can be found here https://github.com/maximegalon5/Data-Products