Model Definition

\[y_i = \beta_0 + \beta_1 x_{1,i} + \beta_2 x_{2,i} + \epsilon_i\]

\(y = Income\), \(x_1 = University\), and \(\epsilon_i \sim N(0, \sigma^2)\).

Model

stan_glm
 family:       gaussian [identity]
 formula:      pay ~ uni
 observations: 12476
 predictors:   14
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                    Median  MAD_SD 
(Intercept)         56098.2   835.6
uniCalifornia       -1330.8  1390.9
uniCheyney           -802.2  1956.5
uniClarion           1429.4  1371.4
uniEast Stroudsburg  2828.3  1387.0
uniEdinboro          1344.0  1324.1
uniIndiana           4376.4  1136.7
uniKutztown          2280.4  1236.6
uniLock Haven        3469.0  1495.2
uniMansfield        -1582.1  1572.7
uniMillersville     -2017.5  1264.7
uniShippensburg      3087.8  1257.2
uniSlippery Rock     3523.2  1297.5
uniWest Chester      -927.7  1093.2

Auxiliary parameter(s):
      Median  MAD_SD 
sigma 29497.1   190.5

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* For help interpreting the printed output see ?print.stanreg
* For info on the priors used see ?prior_summary.stanreg
Characteristic Beta 95% CI1
uni
    Bloomsburg
    California -1,331 -3,956, 1,181
    Cheyney -802 -4,497, 2,945
    Clarion 1,429 -1,365, 4,097
    East Stroudsburg 2,828 171, 5,555
    Edinboro 1,344 -1,272, 4,006
    Indiana 4,376 2,035, 6,610
    Kutztown 2,280 -356, 4,798
    Lock Haven 3,469 453, 6,389
    Mansfield -1,582 -4,925, 1,515
    Millersville -2,017 -4,564, 498
    Shippensburg 3,088 584, 5,586
    Slippery Rock 3,523 977, 6,073
    West Chester -928 -3,154, 1,182
1 CI = Credible Interval