notes08_critique

Build a linear (or generalized linear) model as you like Use whatever response variable and explanatory variables you prefer Use the tools from previous weeks to diagnose the model Highlight any issues with the model Interpret at least one of the coefficients

Select an interesting binary column of data, or one which can be reasonably converted into a binary variable This should be something worth modeling Build a logistic regression model for this variable, using between 1-4 explanatory variables Interpret the coefficients, and explain what they mean in your notebook (Bonus) Using the Standard Error for at least one coefficient, build a C.I. for that coefficient, and interpret its meaning Consider a transformation for any explanatory variable, and illustrate why you need the transformation (or why you do not) Scatter Plots ...

Devise a null hypothesis for an ANOVA test given this situation. Test this hypothesis using ANOVA and summarize your results. Build a linear regression model, run appropriate hypothesis tests and summarize their results.

DataDive6

Data dive 5

sampling and drawing conclusions

Midwest dataset exploring samples

chikweight datadive