讲解SDGB 7840、Modeling Literacy辅导、讲解R编程设计、辅导R语言 辅导R语言编程|解析Java程序
- 首页 >> 其他 HW 3, SDGB 7840: Modeling Literacy Rate
Due: 3/28 in class
Submit THREE files through Blackboard: (a) .Rmd R Markdown file with answers and
code, (b) Word document of knitted R Markdown file, and (c) your data file. Your code/Word
files should be named as follows: “HW[X]-[Full Name]-[Class Time]” and include those details
in the body of those files.
Complete your work individually and comment your code for full credit. For an example of
how to format your homework see the files posted with Lecture 1 on Blackboard. Show all
of your code in the knitted Word document.
In this assignment you will use multiple regression to model the literacy rate across countries;
the goal is to understand which factors might be related to the literacy rate.
Use the data provided by the World Bank to determine which 10 explanatory variables to
consider (http://data.worldbank.org/indicator; and click here for the link to literacy
rate data: link). (This data requires a lot of cleaning.)
Write your paper as a research report. It should be no longer than 8 pages (this includes
graphs and tables but not references) and should include the following six sections. Any
pages beyond the 8th page will not be graded. You can use the posted paper, “The regional
dimension of MNEs’ foreign subsidiary localization” by Arregle, Beamish, and Hebert (2009)
as an example of how to determine what information is important to include in a report.
1. Executive Summary: short paragraph summarizing your paper (this is like the business
version of the abstract in the Arregle, et al paper).
2. Introduction: define the literacy rate and the purpose of the study
13. Data: source of your data; discuss which 10 explanatory variables you considered and
why (not just the ones you ended up including in your final model); relevant summary
information about the explanatory and response variables; which countries are included
in your data set; which year(s) are included in your data set; how you cleaned your
data.
4. Methods: relevant plots; model building summary (transformations, variable selection,
collinearity, etc.); check regression assumptions; model evaluation; relevant hypothesis
tests (include hypotheses, test statistic, degrees of freedom, p-value, α value and
conclusion)
5. Discussion: final regression model; interpretation of model; discussion of usefulness of
model; any ideas you have for improvement
6. References: cite the World Bank as your data source and any other publications you
may have used to learn about the response variable or which explanatory variables
may be helpful, etc. (Note: you do not have to use other sources, but if you do, cite
them.) Your reference list is not included in the 8 pages. Finally, DO NOT COPY
TEXT from sources; write your report in your own words and add citations.
Page 2 of 2
Due: 3/28 in class
Submit THREE files through Blackboard: (a) .Rmd R Markdown file with answers and
code, (b) Word document of knitted R Markdown file, and (c) your data file. Your code/Word
files should be named as follows: “HW[X]-[Full Name]-[Class Time]” and include those details
in the body of those files.
Complete your work individually and comment your code for full credit. For an example of
how to format your homework see the files posted with Lecture 1 on Blackboard. Show all
of your code in the knitted Word document.
In this assignment you will use multiple regression to model the literacy rate across countries;
the goal is to understand which factors might be related to the literacy rate.
Use the data provided by the World Bank to determine which 10 explanatory variables to
consider (http://data.worldbank.org/indicator; and click here for the link to literacy
rate data: link). (This data requires a lot of cleaning.)
Write your paper as a research report. It should be no longer than 8 pages (this includes
graphs and tables but not references) and should include the following six sections. Any
pages beyond the 8th page will not be graded. You can use the posted paper, “The regional
dimension of MNEs’ foreign subsidiary localization” by Arregle, Beamish, and Hebert (2009)
as an example of how to determine what information is important to include in a report.
1. Executive Summary: short paragraph summarizing your paper (this is like the business
version of the abstract in the Arregle, et al paper).
2. Introduction: define the literacy rate and the purpose of the study
13. Data: source of your data; discuss which 10 explanatory variables you considered and
why (not just the ones you ended up including in your final model); relevant summary
information about the explanatory and response variables; which countries are included
in your data set; which year(s) are included in your data set; how you cleaned your
data.
4. Methods: relevant plots; model building summary (transformations, variable selection,
collinearity, etc.); check regression assumptions; model evaluation; relevant hypothesis
tests (include hypotheses, test statistic, degrees of freedom, p-value, α value and
conclusion)
5. Discussion: final regression model; interpretation of model; discussion of usefulness of
model; any ideas you have for improvement
6. References: cite the World Bank as your data source and any other publications you
may have used to learn about the response variable or which explanatory variables
may be helpful, etc. (Note: you do not have to use other sources, but if you do, cite
them.) Your reference list is not included in the 8 pages. Finally, DO NOT COPY
TEXT from sources; write your report in your own words and add citations.
Page 2 of 2