For those curious, I'm using the dataset attached to this post.

So I was told in this problem to fit simple regression models with kid_score being the response variable and all the mom categories being the explanatory variables and determine what the coefficients say about the statistical significance between the two variables. So here's on of the models I made:

Code:

`mom_iq.lm <- lm(kid_score ~ mom_iq, data=IQ)`

Code:

```
summary(mom_iq.lm)
Call:
lm(formula = kid_score ~ mom_iq, data = IQ)
Residuals:
Min 1Q Median 3Q Max
-56.753 -12.074 2.217 11.710 47.691
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25.79978 5.91741 4.36 1.63e-05 ***
mom_iq 0.60997 0.05852 10.42 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 18.27 on 432 degrees of freedom
Multiple R-squared: 0.201, Adjusted R-squared: 0.1991
F-statistic: 108.6 on 1 and 432 DF, p-value: < 2.2e-16
```