Goes over the data of teams stats that qualify football teams for conference championships in the Big 12.

This analysis uses linear regression to examine how selected predictor variables affect miles per gallon (MPG) in the mtcars dataset. After fitting a multiple regression model, I evaluated the statistical significance of the predictors, interpreted the coefficients substantively, and assessed the validity of the model using standard diagnostic plots. These steps ensure that the regression results are both meaningful and statistically reliable.

This analysis examines state level FY2023 Maternal, Infant, and Early Childhood Home Visiting (MIECHV) data, combined with American Community Survey poverty estimates, to understand how resources and reach vary across states. The work integrates descriptive statistics, regression modeling that is informed by causal inference concepts, and equity and efficiency diagnostics.

Danna caldas Laura Manyoma

Testing the regime in which we might prefer inverse-variance weighted median based stacking over traditional inverse-variance weighted mean stacking. The is particularly useful in astronomy applications with large fractions of outlier data (image and spectral stacking).

Coursera Reproducible Research Project 2