It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
Getting Started in Data Analysis: Stata, R, SPSS, Excel: Stata
A self-guided tour to help you find and analyze data using Stata, R, Excel and SPSS. The goal is to provide basic learning tools for classes, research and/or professional development
For courses in introductory econometrics. This package includes MyLab Economics. Engaging applications bring the theory and practice of modern econometrics to life Ensure students grasp the relevance of econometrics with Introduction to Econometrics -- the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics. Also available with MyLab Economics By combining trusted author content with digital tools and a flexible platform, MyLab(tm) personalizes the learning experience and improves results for each student. Note: You are purchasing a standalone product; MyLab Economics does not come packaged with this content. Students, if interested in purchasing this title with MyLab Economics, ask your instructor to confirm the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab Economics, search for: 0134610989 / 9780134610986 Introduction to Econometrics Plus MyLab Economics with Pearson eText -- Access Card Package, 4/e Package consists of: 0134461991 / 9780134461991 Introduction to Econometrics 0134543939 / 9780134543932 MyLab Economics with Pearson eText -- Access Card -- for Introduction to Econometrics
"These pages contain example programs and output with footnotes explaining the meaning of the output. This is to help you more effectively read the output that you obtain and be able to give accurate interpretations."
"Aims of the module: * To provide an introduction to the analysis of spell duration data (‘survival analysis’); and * To show how the methods can be implemented using Stata, a program for statistics, graphics and data management.The foc
Date variables, Granger causality, cointegration test, QLR or sup-Wald test to detect unknown breaks, serial correlation, white-noise, Chow test, cross-correlation and more...
"The [DW] test statistic tests the null hypothesis that the residuals from an [OLS] regression are not Autocorrelated against the alternative that the residuals follow an AR1 process"
"...the short answer is that you estimate your model using regress, vce(robust) and then use Stata’s test command. You then call the result a Wald test. "
"A Chow test is simply a test of whether the coefficients estimated over one group of the data are equal to the coefficients estimated over another..."
"F and chi-squared statistics are really the same thing in that, after a normalization, chi-squared is the limiting distribution of the F as the denominator degrees of freedom goes to infinity."
"This issue focuses on time series models, with special emphasis on the tests of Granger causality. I am providing instructions for both R and STATA. I would like to remark that the theoretical background given in class is essential to proceed with the ..
"Stata’s new mi command provides a full suite of multiple-imputation methods for the analysis of incomplete data, data for which some values are missing. mi provides both the imputation and the estimation steps. mi’s estimation step encompasses both estimation on individual datasets and pooling in one easy-to-use procedure."
"One of the most common mistakes made when analyzing data from sample surveys is specifying an incorrect type of weight for the sampling weights. Only one of the four weight keywords provided by Stata, pweight, is correct to use for sampling weights."
"This issue focuses on time series models, with special emphasis on the tests of unit roots and cointegration. I am providing instructions for both R and STATA. I would like to remark that the theoretical background given in class is essential to proceed.
"New in Stata 12 is the marginsplot command, which makes it easy to graph statistics from fitted models. marginsplot graphs the results from margins, and margins itself can compute functions of fitted values after almost any estimation command, linear or nonlinear."
"tabout is a Stata program for producing publication quality tables.1 It is more than just a means of exporting Stata results into spreadsheets, word processors, web browsers or compilers like LATEX. tabout is actually a complete table building program"
"Estimation commands provide a t test or z test for the null hypothesis that a coefficient is equal to zero. The test command can perform Wald tests for simple and composite linear hypotheses on the parameters, but these Wald tests are also limited to tests of equality."
"Linear dynamic panel-data models include p lags of the dependent variable as covariates and contain unobserved panel-level effects, fixed or random." [Source: http://www.stata.com/help.cgi?xtdpd"
"In addition to providing built-in commands to fit many standard maximum likelihood models, such as logistic, Cox, Poisson, etc., Stata can maximize user-specified likelihood functions."
"prod provides a multiplicative function for egen analogous to the additive sum function. The product of all non-missing observations of meeting optional in and if conditions is returned in for each observation meeting the conditions. would most commonly be an existing variable in the data set. This is version 1.3.4 of the software."
"As of version 9, Stata contains a full-fledged matrix programming
language, Mata, with all of the capabilities of MATLAB, Ox or GAUSS. Mata can be used interactively, or Mata functions can be developed to be called from Stata."