Two Parameters

Author

Zephan S

Using data from the NHNES that includes 15 variables, such as height and weight, we seek to create a model of height for adult men. One problem is that, since the survey is voluntary, taller men would be more eager to fill it out. We used the Gaussian model to find the average height for males. We found that there is a 30% chance for the random male to be greater than 180 cm or 5 foot 11 inches.

Characteristic

Beta

95% CI

1
(Intercept) 176 176, 176
1

CI = Credible Interval

 
 Family: gaussian 
  Links: mu = identity; sigma = identity 
Formula: height ~ 1 
   Data: ch5 (Number of observations: 3658) 
  Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
         total post-warmup draws = 4000

Regression Coefficients:
          Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
Intercept   175.87      0.12   175.63   176.11 1.00     3788     2818

Further Distributional Parameters:
      Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
sigma     7.48      0.09     7.31     7.65 1.00     3893     2633

Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
and Tail_ESS are effective sample size measures, and Rhat is the potential
scale reduction factor on split chains (at convergence, Rhat = 1).
# A tibble: 1 × 2
   .row  odds
  <int> <dbl>
1     1 0.297