
Learn the Stata Interface including Results and Command windows, Variables and their Properties. Get acquinted with Data Editor and Do-file Editor. Load Stata .dta file and create a .do file in Stata. Add comments to the Stata .do file.
Learn how to obtain the information about the new dataset, including the descriptive statistics. Practice advanced examples: describe data by group and create tables like Pivot Tables in Excel.
FUNCTIONS COVERED: describe, codebook, summarize, tabulate, table.
Learn how to create two of the most common graphs – histograms and scatter plots. Start from the most basic examples and add extra features and options. Practice advanced examples with graphs split by group, add linear trend, change options.
FUNCTIONS COVERED: histogram, scatter, twoway scatter, lfit, generate, label.
Please use Code1_AmesHouses.do and DataSet1_AmesHouses.dta from the previous video.
Learn how to load Excel files and other data formats into Stata. Create variables using conditional statements and prepare a set of indicator variables from factor variables. Practice preparation of variables for modeling in Stata.
FUNCTIONS COVERED: import excel, replace, drop, xi, rename, label var.
Learn how to install packages from Boston SSC archieve. Create Table 1 with descriptive statistics for different subsamples. Estimate linear probability model for different sub-samples and compactly present the estimation results in a single publication quality table.
FUNCTIONS COVERED: ssc install, estout, global, quietly, estpost, estimates store, esttab, cond, regress.
Please use Code2, DataSet2 and Codebook2 from the previous video.
Speed up your learning of Stata with the help of ChatGPT! Estimate a linear regression, generate variable for values above the median, request a package from Boston SSC archieve.
FUNCTIONS COVERED: regress, generate, histogram, ssc install
Learn how to load .csv files into Stata. Declare time series object and plot time series. Create a trend and seasonal variables. Estimate models with trend and seasonal components. Obtain forecast and residuals and interpret the results.
FUNCTIONS COVERED: tsset, line, predict.
The notion of serial dependence and the definition of lagged variables. Learn how to estimate time series models with lagged variables and interpret the results.
Please use Code3 and DataSet3 from the previous video.
Learn how to get help on Stata questions from Stata help, Stackoverflow and Statalist. Course summary and wrap up.
Jumpstart your Stata journey in 2024 with a new ChatGPT module – great for those learners who want to start right away!
Don't waste a single minute - get ready for your course work, term project or research in no time!
There are many great online courses in Stata that sell in thousands of copies. However, modern life is very fast and learners might not have 10 or more hours to get every single detail in Stata right away. My approach is different – I believe that you need only a few key instruments to start working in Stata.
Based on my 20+ years of experience in Stata I have picked those key tools for this course. In addition, I used my experience of teaching short courses (sometimes as short as just one evening!) for very diverse audiences including students, professionals, and adult learners to save your precious time and to allow quick learning based on examples.
After taking this course you will know how to open .dta, Excel, and .csv files in Stata and save your work in Stata .do files. You will be able to create new variables using conditional statements and recast a factor variable into a set of indicators (one for each factor). You will then create three key graphs – a histogram, scatter plot, and a time series line – with many essential extra features. We will also estimate 10+ regression models of continuous, indicator, and time series variables. Finally, we will learn how to create tables of publication quality which you can immediately insert into your MS Word file. By the end of the course, we will be able to use up to 20 essential Stata commands including those from Boston SSC Archive.
You will learn all these essential skills by running line-by-line 3 codes using 3 real (not fake!) datasets to model house prices in Ames (Iowa), the smoking behavior of Ukrainians based on the Household Budget Survey, and sales of vehicles in the United States over time. The codes contain very detailed comments and explanations which you can use to replicate the commands in your own projects.
Over my entire professional career, I have enjoyed working in Stata and hope that you will share my passion for this great and powerful tool that can help you to prepare engaging term projects, consultancy reports, or academic papers.
Let this course be the first step in this direction!