Class Labs
Links to the labs for each week can be found here, along with links to the cloud folders where the data for the class labs can be downloaded.
Class Lab 1
In This Lab: We cover the basic elements of the Stata workspace, lay out a workflow for conducting analysis in Stata, handle creating and labeling variables, make some basic graphs, and learn to estimate simple summary statics of variables. We use data from the American Time Use Survey (ATUS) to work through these examples in Stata.
Class Lab 2
In This Lab: We review project workflow, making basic graphs, and summary statistics and move into graphing the relationship between two continuous variables with scatterplots and estimating Pearson’s R coefficient. We use data from the American Community Survey (ACS) to work through these examples in Stata.
Class Lab 3
In This Lab: We review graphing and estimating relationships between two continuous variables, and then we cover how to examine relationships between categorical variables using two-way tables. We use data from the Education Longitudinal Study of 2002 (ELS:2002) to work through these examples in Stata.
Class Lab 4
In This Lab: We review working with categorical and continuous variables to create a table. We then walk through the steps to create z-scores in Stata. We use data from the American Time Use Survey to work through these examples in Stata.
Class Lab 5
In This Lab: We review estimating means and standard deviations in Stata, learn new commands to estimate means with standard errors and confidence intervals, and then cover the basics of hypothesis testing in Stata. We use data from the Census of Adult Correctional Facilities to work through these examples.
Class Lab 6
In This Lab: We review estimating summary statistics for subsamples in Stata, walk through using summary statistics to calculate a two-sample t-test, and then using Stata to run a two-sample t-test for us. We use data from Project STAR to work through these examples.
Class Lab 7
In This Lab: We review estimating linear regressions in Stata and interpret the output Stata provides after estimating a regression. We use data from the National Health Inventory Survey to work through the example.
Class Lab 8
In This Lab: We review estimating simple, bivariate linear regressions in Stata and interpret the output Stata provides after estimating a regression. We then move on to adding additional control variables to our models to estimate a multivariate regression model. We use data from the ATUS to work through the example.