Rstudio, data analyzing

| March 11, 2014

[meteor_slideshow slideshow=”adssa” metadata=”height: 126, width: 630″]
Order Details
Data analysis project “dry run”
Format: Please submit a SINGLE document (docx or pdf) containing your answers to all questions, with your complete R script copied and pasted to the end of the document. Your R script should include your name, the date, a brief description or title, and all the commands needed to create ALL the output for your assignment, as well as comments (#). Please make sure not to repeat any errors noted in your previous assignments.
Introduction: This assignment is a “dry run” of the regressions you plan to use in the final report of your Data Analysis Project. Your regressions should be presented in one or two mtables in a document, with accompanying discussion of the specifications and results. The document should discuss every regression in your table(s).
Read the final project assignment so you know what you need to do. The overall task for the final project is:
Write and submit a report, backed up by statistical analysis of the 2011 ACS data set, exploring the gender earnings gap among college graduates. Is there currently a gap between the earnings of male and female workers? Does that gap persist when we control for other worker characteristics correlated with earnings? Does the size of the gender gap vary by worker characteristics?
For this assignment (#8), do the following:
In a paragraph or two, describe your regression model of earnings: How do you plan to use regression(s) to estimate the gender gap and its determinants? What are your key variables (dependent variable and regressors)? How do you plan to determine whether the gender gap varies by worker characteristics?
You should start with a base specification. You may, if you like, start with a version of one of Weinberger’s regressions, augmented as you see fit.
Run a few alternative specifications to examine the impact of additional regressors/ controls, nonlinear specifications, interactions, etc. You could also consider running separate regressions for males and females. Explain the choices you have made. Discuss the results: Make sure to assess the statistical significance and magnitude of the effects. What do you learn about the gender gap and its determinants? Make sure your text refers to and interprets each regression. Number or label your regression columns and refer to specific regressions by number when discussing them in the text.
Be prepared to discuss what you did in the lab class.
You will be free to change your regressions for your final report… this is just to get you started.
below is the final project which related in top assignment
1. A written essay, maximum of 2000 words, double-spaced, with the following components:
Executive summary: One paragraph summarizing your research questions and findings
Short introduction and overview of the issue of the gender earnings gap, drawing on your readings, and an overview of the ACS data set
Description of your regression model of earnings: How do you plan to use regression(s) to estimate the gender gap and its determinants? What are your key variables (dependent variable and regressors)? How do you plan to determine whether the gender gap varies by worker characteristics?
Discussion of regression results (refer to regression tables)
Base specification(s): You could, for example, start with something like Weinberger’s model (1), but you are free to do what you like.
Alternative specifications and extensions: Try additional variables or different functional forms; consider whether the gender gap varies by worker characteristics. Explain briefly why you did what you did.
Discuss your findings:
What is your preferred specification?
What do your regressions tell you about the gender gap? Do your results shed any light on the role of qualifications vs. discrimination?
Discuss whether your findings are consistent under alternative specifications.
Internal and external validity: Discuss potential threats to the internal and external validity of your analysis, especially potential sources of bias. Use Chapters 8 and 9 of Stock and Watson as your guide.
Conclusions
2. Tables and figures:
At the end of the written essay, add your tables and figures. You may include up to two (2) tables of regression results, each table containing no more than six (6) regressions, and up to four (4) figures (plots). These are maxima: You DO NOT have to include this many! Please format the tables so the columns line up and I can easily read them (it helps to use a font like Courier or Lucida for the tables).
This assignment is using acs_data_bach.csv data. and i will upload the tutorial documents provided by the professor, you can refer to that.
[meteor_slideshow slideshow=”best” metadata=”height: 126, width: 630″]

Get a 5 % discount on an order above $ 150
Use the following coupon code :
2018DISC
Describe your Company’s Intranet
Data Analysis Using both Excel and Stata

Tags: , ,

Category: Information Technology

Our Services:
Order a customized paper today!