AVD Raj A Please go through instructions carefully In the 1st document, I need the outline covering all the Professor’s requirements. In the 2nd docu

AVD Raj A
Please go through instructions carefully
In the 1st document, I need the outline covering all the Professor’s requirements.
In the 2nd document, I need the research paper covering all the Professor’s requirements.
Outline for Assignment 1
Using the research guide and the assignment 1 instructions, develop your outline. Submit the outline in an MS Word document file type. Utilize the standards in APA 7 for all citations or references in the outline. Ensure that the document includes your name. Do not include your student identification number. You may use the cover page from the student paper template, but it is not required. The assignment 1 instructions are at the bottom of this content folder.
Submit your outline on or before the due date.
By submitting this paper, you agree:
(1) that you are submitting your paper to be used and stored as part of the SafeAssign services in accordance with the Blackboard Privacy Policy;
(2) that your institution may use your paper in accordance with UC’s policies; and
(3) that the use of SafeAssign will be without recourse against Blackboard Inc. and its affiliates.

4/24/20 Assignment 1 AZ UT.docx P a g e | 1

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Research Assignment 1
The Outline for Research Assignment 1 and Research Assignment 1 will use this document.

Use the Documenting Research Guide to understand how to use the information in this document for

either of these submissions.

Ask questions if needed!

Topic: The Center for Disease Control and Prevention (CDC) uses the social vulnerability

index (SVI) to evaluate the impact of disasters on communities, weighting the damage

with social factors in the states of Arizona and Utah.

Problem: The data consolidated by the CDC is used to determine the most vulnerable areas

should a disaster occur. In a perfect world, the indicators of vulnerability would

represent the people correctly. Currently, this far-from-perfect method is the best that

has been developed. There may be indicators that are not adequately predictive of

social vulnerability.

Question 1: What relationships exist in the states of Arizona and Utah between the socioeconomic

indicators, household, and composition indicators, disability indicators, and social

vulnerability when using the data consolidated by the CDC (2018a)?

Question 2: What indicators in the states of Arizona and Utah between the socioeconomic

indicators, household, and composition indicators, disability indicators have the most

influence in predicting social vulnerability when using the data consolidated by the CDC

(2018a)?

Data:

The data and data dictionaries are online.

o Center for Disease Control and Prevention. (2018a). Social Vulnerability Index [data

set]. https://svi.cdc.gov/Documents/Data/2018_SVI_Data/CSV/SVI2018_US.csv

o Center for Disease Control and Prevention. (2018b). Social Vulnerability Index [code

book]. https://svi.cdc.gov/Documents/Data/2018_SVI_Data/SVI2018Documentation.pdf

o Note: The raw data must be this report in its original form when it enters the R script

file. Use the data dictionary to understand the data.

Create a subset of the data to represent the sample of secondary data in this analysis.

o The SVI indexs variable name is

RPL_THEMES, in column 99

o Socioeconomic

Persons below the poverty

estimate

Civilian unemployed estimate

Per capita income estimate

Persons with no high school

diploma

o Household and composition disability

features

Ages 65 and older

Ages 17 and under

Persons with a disability, over the

age of 5

Single-parent households

o The state field

4/24/20 Assignment 1 AZ UT.docx P a g e | 2

Note: Do not use more than one indicator for each measure defined in this section.

Variable names preceded with E_ are actual measures, while M_ represents the

margin of error estimates.

Other prefixes are follow-on calculations or qualitative information, do not include variables

that are not identified in the research questions, as listed in the data section.

Do not include the margin of error estimates at this time.

Considering the research questions, after subsetting, there will be 10 variables used in this

analysis.

Data Cleaning:

Do not remove missing values during cleaning. If missing values need to be removed for

analysis method, do it during the preparation for analysis. A code represents missing values.

Use the data dictionary to understand the data sample and how missing values are

represented.

When changing an object or part of an object, validate the change that occurred as expected.

The steps that are taken in cleaning are not discussed in the research paper.

There is a code that represents missing values; ensure this is found in the data dictionary!

These values will have to be recoded as NA. Not figuring it out? Please email me.

Analyze:

Conduct two types of analysis: visual analysis to identify relationships and a random forest

model to identify influential indicators in predicting the social vulnerability.

The sub-stages of Analyze are necessary at least two times; profile, prepare, and apply. This

method is for programming, not documenting research.

During the visual analysis, only present meaningful visuals to understand what the

relationships exist between the indicators for the social vulnerability index.

Ensure you establish that the model is valid and reliable before discussing the influential

indicators.

Documenting research:

Results, Impact of the Results:

Ensure that assertions and assessments in the results and discussion sections are derived

from the analysis in R.

Do not speculate. Use evidence. When documenting the results, consider the generalizability.

Future Recommendations:

Include recommendations for future analysis, based on the research in R.

An example might look something like this:

o An opportunity for further research, based on gaps found in the random forest modeling,

is to look at the ability to tune the parameters further, to improve the performance in

predicting the

o Additionally, an opportunity for future research is exploration modeling to determine

what other variables, when eliminated, have little or no impact on the ability to predict

the SVI based on the supporting characteristics in the data.

4/24/20 Assignment 1 AZ UT.docx P a g e | 3

Bonus challenge:

Create a random forest model for each state that is assigned. Ensure that this analysis is within the

scope of the research.

Tip: An additional research question that meets the five criteria from the first lecture will bring

this analysis within the scope. Make sure the question is structured to encompass the additional

research. The challenge does not replace the original research requirements for this assignment.

Required files to submit:

1) Research paper in APA 7 format; MS Word document file type

2) R Script; final version

Important Information:

You will receive an email confirming the submission. Should you receive that email, your

submission is received.

o An error is derived from the use of SafeAssign. SafeAssign does not recognize r file

types. The warning does not impact the submission.

The research paper will be written in a professional writing style, following APA 7 student

paper format, use the student paper template.

o The document shall be 3-5 pages and at least 1000 words. The page count does

include the cover page, tables, or figures, or the reference page.

o Ensure that every reference in the reference list is also cited in the text.

o Do not forget to cite and reference the source of the data.

It is ill-advised to modify the problem statement and research questions provided.

If the research problem or research questions are modified, the requirements of the analysis

will not change.

There are several different versions of this assignment. If the submitted work is in line with a

different version than assigned, the submitted work is a demonstration of academic

dishonesty. Do not share the work with peers. Do not accept work that you did not do.

Take a look at the rubric to get the best grade possible. Documenting Research Guide Last Revised: 8/30/2020 1

Documenting Research Guide

Contents
Outline Structure and Content ……………………………………………………………………………………………………………….. 2

Outline Example coinciding with Unit 3 …………………………………………………………………………………………………. 4

Writing Tips ………………………………………………………………………………………………………………………………………… 7

Example Research Paper coinciding with Unit 3, annotated ………………………………………………………………………. 8

Example Research Paper coinciding with Unit 3 ……………………………………………………………………………………. 22

Documenting Research Guide Last Revised: 8/30/2020 2

Outline Structure and Content
The outline is an organization document to provide structure for the research paper. Use the outline to document

research.

Section 1, Level 1 Section Heading: This heading is the title of the paper.

Background, topic, introduction

Describe the broader context in which the problem exists, the topic

Lead the reader to the problem statement

Do not explicitly state the problem, research questions, or methodology

This section introduces the research topic and provides a high-level summary of what the reader can expect

to find in the rest of the paper.

Section 1, Level 2 Section Heading: Statement of the Problem

This section may come straight from an assignment’s instructions

Provide the ideal, current, and intent of the problem for research

Section 2, Level 1 Section Heading:Research Methodology

Begins with an introduction to all the content in the research methodology section

Section 2, Level 2 Section Heading: Research Questions

This may come straight from the assignment’s instructions

Ensure that developed questions conform to the standards defined in the first lecture

Section 2, Level 2 Section Heading: Sample Data

Review the sample data variable names do not identify what the content represents so do not use

variable names!

Explain and describe what each of the variables represents, connecting the sample to the

background, problem, and question so the reader can understand what the data represents and why it

is suitable data to answer the research questions

Section 2, Level 2 Section Heading: Analysis Method and Limitations

A plan, defining what type of analysis will address each research question.

The plan will include statistical assumptions, limitations to the analysis method, and mitigating steps

taken for the limitations.

This section is not a programming plan! This section does not include the programming procedure or

steps. Define this section before conducting any programming or analysis.

This section finishes with a summary of the content of the section

Develop everything above this statement is before analysis. Work on everything below after the analysis.

EXCEPTION: Develop the reference section before and after analysis.

Some of the elements above this statement could change after analysis.

Section 3, Level 1 Section Heading:Results and Discussion

Begins with an introduction to all the content in the results and discussion section

Documenting Research Guide Last Revised: 8/30/2020 3

This objective of the research is to answer the research questions the purpose of this section.

o If there is more than one research question, address them individually

o Pay attention to the generalizability!

Provide interpretations of all results!

Inclusion of figures or tables must conform to APA 7 standards

Include all findings, even if they do not support the desired outcome

o If the analysis method for the findings has statistical assumptions, address the statistical

assumptions before presenting the findings

There is no programming code in this section.

Finishes with a summary of the content in this section

Section 3, Level 2 Section Heading: Recommendations for Future Research

After the analysis, how can it be improved?

Different analysis methods?

Different sample data?

Different data structures?

The recommendations must come from the research; do not recommend different data collection methods that

is not part of the research! (This course only uses secondary data, data consolidated by someone else.)

Section 4, Level 1 Section Heading:Conclusion

The conclusion is a summary of everything in the entire paper

Do not introduce new ideas in the conclusion

Highlight key points of the research or findings

Section 5, Level 1 Section Heading:References

Reference section and references per APA 7

Some of the standards for this section per APA 7

o References always begin on a new page

use insert new page to ensure this section starts at the top of a separate page from the rest

of the document

o References are in alphabetical order

o Annotated with a hanging indent

The reference begins flush with the left one-inch margin

Indent wrapped text is one-half inch

Documenting Research Guide Last Revised: 8/30/2020 4

Outline Example: based on the analysis in Unit 3

The 2016 Presidential Campaign Polling

The 2016 election was tumultuous

o Distinct perception Trump would not win

o Bias may have played a part

o Polling samples

o shy voters

The research includes analysis of the polls’ results and how the

results relate to the outcome of the election.

Statement of the Problem

Neutral polling, collected from a sample genuinely representative of

the voters, will provide an accurate prediction of the winner of an

election. Polling seemed to indicate that Clinton was going to win,

but the electoral vote significantly favored the Trump campaign.

Exploration of the polling results throughout the campaign and a

particularly close look at the ratings at the end of the campaign may

provide insight into the source of the significantly different outcome

than the media portrayed with the election of President Trump.

Research Methodology

Research Question

Considering the 2016 presidential campaign, using the polling data

consolidated by Silver et al. (2016) and the election results

consolidated by Ballotpedia. (n.d.), what relationships exist between

the polling and the 2016 election results that indicate that President

Trump would win the election?

Sample Data

Note: Keep in mind that if the data used in an assignment has

variables not used in the analysis, those variables are not part of the

sample! Take note of this in the data. There are several fields not

discussed here, because the fields were not part of the analysis

The secondary sample data from Silver et al. (2016) includes

polling data that represents

o Location: fifty states, national polls, and Washington

DC

o Dates: November 2015 to November 2016, the ending

date for each poll

o Size: the sample size of each poll

The title is capitalized in

title case. This is the

first section heading and

the title of the paper in

the final document.

For most of the course this is

provided. In the outline and

research paper, the entire

statement is provided.

Cite the source(s) of the

sample data.

Provide a summary of the

document in the introduction.

While the outline has sentence fragments and bullets throughout the research paper will not. The

organizational statements in the outline are written as well-developed paragraphs in the research paper.

In APA 7, a level 1

section heading is in

bold, centered between

the one inch left and

right margins.

In APA 7, a level 2

section heading is in

bold, flush to the one

inch left margin.

All research questions

belong in the outline.

Explain the sample in

words.

Explain how the data is

represented, such as parts

per million or percentage

of votes.

Documenting Research Guide Last Revised: 8/30/2020 5

o Vote: the percentage of votes for President Trump

and for Clinton each poll in the data

The secondary sample data used from Ballotpedia (n.d.)

represents:

o fifty states and Washington DC

o electoral votes available in each state

o 2016 election vote percentage of each state for

President Trump and Clinton

Analysis Method and Limitations

What relationships exist between the pre-election polling attributes, the

2016 election, and each state’s allocated electoral votes that indicate that

President Trump would win the election?

assessed via visual analysis

o not parametric, therefore no statistical assumptions

o limitations of visual analysis

high dimensionality is challenging to assess

possibility of inadequate assessment leading to

incorrect conclusions

the more comparisons, the higher likelihood of false

discoveries (Zhao et al., 2017)

o mitigation for inadequate assessment

explore interesting findings via multiple facets, to

ensure adequate assessment

o mitigation for false discoveries

Attempt to view any key finding from multiple

perspectives, to validate the finding

Develop everything above this statement for the outline, along with the

reference section.

Develop everything below after the analysis, along with the reference

section. There may be updates to the other sections.

Type of analysis for each research

question; list each question!

Declare how this method can

address each of the research

questions.

Declare any statistical assumptions

for this method of analysis with a

credible reference.

Provide limitations to the method

of analysis and methods to

mitigate limitation if it impacts

the validity or reliability of the

research.

In other words, if the limitation

can lead to incorrect conclusions,

how will correct conclusions be

determined?

Declare the headings for

the remaining fields

The design for analysis

Documenting Research Guide Last Revised: 8/30/2020 6

Results and Discussion

Recommendations for Future Research

Conclusion

References

Include the reference(s) of the data, in APA

7.

Include a citation for every

reference

Include a reference for every

citation

The reference section begins on a separate page.

Documenting Research Guide Last Revised: 8/30/2020 7

Writing Tips
When writing a paper or developing a presentation, always include a summary of the document within

the introduction and the conclusion.

Focus the writing on the purpose: solve the problem, answer the question, or prove the expected
outcome. In this course, the assignments will all have research questions. Focus on the questions.

Write concisely. This is not a persuasive paper. Writing superfluously devalues your work.

When you finish writing:
o Read the document aloud.

This is the single, most effective method to identify elements of the document that
require editing.

Think about the problem, research questions or the expected outcome:

Did you focus on it throughout the document?

Did you provide answers to the research question(s)?
o If you are not particularly confident in your writing:

Take time to identify the topic sentence in every paragraph, in every section, and within
the introduction and conclusion.

There should be transition sentences between the ideas in the document. Does the writing
jump from one idea to the next?

The writing center is an excellent resource, as well.
Use the outline to organize your graduate-level writing.

Do not concern yourself with your SafeAssign score.

o Ensure that quoted words, paraphrasing, and direct references to external sources have citations

and references to the original source of the information. Still not sure? Email me.

o Think about it! What do you think the average SafeAssign percentage is for the outline?

A significant portion of the outline will come from the assignment instructions.

The matching criteria from SafeAssign typically allocates 60-80% scores to submissions

that are correctly written.

Cite every reference. Include all references in the reference section.

Evaluation of all writing assignments by APA 7 criteria.

o Student papers do not include an abstract.

o Vertical spacing is uniform between lines of text

Microsoft Word automatically adds paragraph padding remove it or use the template.

o The text alignment throughout the document is left-align, not justify.

o Do not solely rely on citation and reference generators. These tools are fallible.

8

Documenting Research Guide Last Revised: 8/30/2020 8

Example Research Paper: with notations

The 2016 Presidential Campaign Polling

Dr. Kathy A. McClure

University of the Cumberlands

ITS-530: Data Analysis and Visualization

Dr. Kathy A. McClure

July 23, 2020

One of two places in the

document correctly

documented with non-

uniform vertical spacing.

.

The top name is author.

When you see my name

again it is for the

professor of the course.

The only element in the header is the page number in the

same font as the document, starting at 1. (As this is part of

an example document the numberling is different.)

There is no footer in the student research paper.

There is no footer in a student research paper, per APA 7.

This footer is for document control.

9

Documenting Research Guide Last Revised: 8/30/2020 9

The 2016 Presidential Campaign Polling

The 2016 presidential campaign was tumultuous. It had seemed impossible that President

Trump would win the election. Silver et al. (2016)

indicated that there was a 71.4% chance that Clinton

would win the election. During the campaign, the media

led voters, including elected members of the republican

party, to believe that President Trump would not win the

election (Hohman, 2016). Regardless of the media,

Hohman (2016) retroactively identified that there were

many voters that were not pro-Clinton leading up to the

election. Stevenson (2016) interviewed American

University professor Dr. Allan Lichtman, who overtly

stated that President Trump would win the election based

on historical voting in this country. Dr. Lichtman

specified to exceptions to this claim: candidate Johnson

must receive at least five percent of the vote and

President Trump’s unpredictable behavior. Goldmacher and

Schreckinger (2016) stated that President Trump winning

the election was the “biggest upset in U.S. history”

(title). Many believed Clinton would win.

Problem Statement

Polling samples that represent the population will

provide an accurate prediction of the election winner.

Note that the outline was not followed

explicitly for the topic/introduction

Dont forget to cite and reference sources

of information

Use evidence to support any assertions

that are not common knowledge

Example: Sampling bias was an issue in

all polls. That statement infers this is a

fact when it is not and it would be

impossible to prove this statement!

You must have a citation and reference for

assertions.

From the outline:

The 2016 election was tumultuous

Distinct perception Trump would
not win

Bias may have played a part

Polling samples

shy voters

The research includes analysis of
the polls’ results and how the results

relate to the outcome of the election

Why did this quote end with the word title

in parentheses? It is cited correctly. The

statement began with the source authors and

date. A quote requires three parts in the

citations, author, data, and the page number.

The reference is a website, so there are no

page or paragraph numbers. It must identify

where the quote was found, in this case, the

title.

The problem statement is verbatim from the

outline, unless it was insufficient.

10

Documenting Research Guide Last Revised: 8/30/2020 10

Polling results appeared to indicate that Clinton was going to win, but the election resulted in

President Trump swearing-in as the 45th president. Exploration of the polling and election results

may provide insight as to why the election winner was unexpected.

Method

Research Question

Considering the 2016 presidential campaign,

using the polling data consolidated by Silver et al. (2016)

and the election results consolidated by Ballotpedia. (n.d.), what relationships exist between the

polling and the 2016 election results that indicate that President Trump would win the election?

Sample

This research employed two secondary data sources

for the analysis. Consolidated polling data collected by

Silver et al. (2016) is the first data source. Each observed

poll includes the percentage of votes by location, ending

date, and sample size for Clinton and President Trump.

Ballotpedia (n.d.) election data is also necessary for this

analysis and includes the percentage of votes by location

for Clinton and President Trump. Available electoral

votes for each location is another attribute in the election

data. Locations between the two secondary data sources

differed.

The polls’ locations include the entire nation, each

state, and Washington, DC, and specific districts within Nebraska and Maine. The district polls

The research question(s) are verbatim from

the outline unless the question was

insufficient.

From the outline:

The secondary sample data from

Silver et al. (2016) includes polling

data that represents

fifty states, national polls, and
Washington DC

November 2015 to November
2016, the ending date for each poll

the sample size of each poll

provides a raw percentage of votes
for each poll for President Trump

and Clinton

The secondary sample data used from

Ballotpedia (n.d.) represents:

fifty states and Washington DC

electoral votes available in each
state

2016 election vote percentage of
each state for President Trump and

Clinton

11

Documenting Research Guide Last Revised: 8/30/2020 11

within Nebraska and Maine were representative of the method of electoral vote distribution.

Splitting the electoral vote is possible in Nebraska and Maine (Coleman, 2020). In the other 48

states and Washington, DC, using winner-take-all, the

popular vote winner for the state receives all the electoral

votes. The election data simplified the locations: each

state and Washington, DC.

Analysis Method and Limitations

The method of analysis must be suitably capable

of meeting the objective of this research, statistical

assumptions identification is necessary, if they exist, and

identification of any limitations is essential, along with

mitigation, where possible. Visual analysis is suitable for

extracting relationships that may exist in the data. This

method is also appropriate for confirming the information

derived from the analysis. There are no formal statistical

assumptions. There are three limitations identified for visual

analysis.

High dimensionality, inadequate assessment, and false discoveries are risks associated

with visual analysis. The scope of this research does not include numerous variables, mitigating

the threats associated with high dimensionality. The potential for inadequate assessment and

false discoveries requires mitigation. Visualizations of data provide a perspective of the

information without context. To mitigate these risks, it is compulsory to assess all key findings

from multiple perspectives. This process ensured that there was an adequate assessment of that

From the outline:

Analysis Method and Limitations

assessed via visual analysis

not parametric, therefore no statistical
assumptions

limitations of visual analysis

high dimensionality is challenging to
assess

possibility of inadequate assessment
leading to incorrect conclusions

the more comparisons, the higher
likelihood of false discoveries (Zhao et

al., 2017)

mitigation for inadequate assessment

explore interesting findings via
multiple facets, to ensure adequate

assessment

mitigation for false discoveries

Attempt to view any key finding from
multiple perspectives, to validate the

finding

12

Documenting Research Guide Last Revised: 8/30/2020 12

the perceived information. Focusing on the research question and using two sources of secondary

data, the analysis generated results.

Results

Consolidation of the visual analysis highlighted key findings through four visualizations

of data. Manipulating the data with various summarization techniques generated meaningful

graphics. The sample included nearly a year’s worth of polling data, but limiting the data to polls

closest to the election generated the key findings in this research. The term polling vote

represents polls ending in November 2016, consolidated by state and candidate, using the median

value. Geospatial visualization indicates that in 45 of the 50 states the winning candidate in the

polling vote and the election were the same (see Figure 1). In five states, Clinton led in the

polling vote, but President Trump won in the

election. For simplification, the term flipped states

refers to the five states identified in Figure 1.

Due to the non-uniformity of the data, the measure of centrality in this analysis is the

median. Summarizing data can cause misrepresentation of the data. Comparing the polling vote

identified 12 states with five percent or less difference between candidates. Visualizing the 12

states identified the how well the median represents the data (see Figure 2). The evidence

suggests that the median does not misrepresent the results. The 12 states include the five flipped

states identified in Figure 1. The close margins in the polling data of the flipped states

necessitated a deeper investigation, into individual polls. Before documenting the remaining

results of this analysis, the visualization of the difference between candidates requires further

explanation.

Repeating the same information is ill-advised.

Dont repeat the information in the caption of a

figure or table.

13

Documenting Research Guide Last Revised: 8/30/2020 13

The candidates were compared by subtracting the polling votes for each state (see Figure

3 and Figure 4). The values direction is indicative of the winning candidate. Leads held by

Clinton are to the left of zero. Where President Trumps led, the value is annotated to the right of

zero. The value is indicative of how much lead one candidate has over the other. For example, if

President Trump earned 40% of the vote and Clinton earned 41% of the vote, Clinton led that

vote by one percent. This Clinton lead would be visualized by placing the marker to the left of

zero on the axis marker representing a value of one percent.

APA use of figures & tables is specific. Each figure or table but include enough information to be self-explanatory.

Do not explain the figure in the document. **You must refer to each figure or table in the document, though!**

Results require EVIDENCE. In visual analysis, the evidence is visual!

14

Documenting Research Guide Last Revised: 8/30/2020 14

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Documenting Research Guide Last Revised: 8/30/2020 15

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Documenting Research Guide Last Revised: 8/30/2020 16

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Documenting Research Guide Last Revised: 8/30/2020 17

After identifying the flipped states polling vote by candidate differed by five percent or

less, each poll within flipped states ending in November 2016 were analyzed (see Figure 3). The

majority of the individual polls also varied by less than five percent

between the candidates. Clinton held the lead in nearly all polls in

these states. In Florida, there were no polls that exceeded the five

percent margin between candidates. Trump did not lead in any polls

in Wisconsin from this data.

The polling vote and election vote were compared by

candidate all election locations from the data. While five states

flipped, there were other states with close margins. Additionally, the

compa

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