HMGT400 TEAM AGREEMENT

Step-By-Step Team Assignment #1

HMGT 400

TEAM AGREEMENT

Before
starting make sure that you have agreement for individual tasking. This is a
team project and all team members are required to have a significant
contribution.

? Start team assignment (TA) early in the next week or even by the end
of this week,

do not postpone it until the weekend;

? Be clear about your contribution for this TA.

? Define the timeline for delivery, e.g., First Draft by Thursday (4/6),
Group Modification by Friday (4/7),

Review by all team by Friday and Saturday, ready to submit by
Saturday.

Team Assignment #1

Start with the cover page (1 page, include name of all group members,
group #,running head, abstract).

Please look at the example: http://www.apastyle.org/manual/related/sample-experiment-paper-1.pdf

Title

All topics approved, so you have your topic and
dataset.

1. Introduction

Introduce the problem or topic
being investigated. Include relevant background information that: indicates why
this is an issue or topic worth researching; highlights how others have
researched this topic or issue (whether quantitatively or qualitatively), and
specifies how others have operationalized this concept and measured this
phenomena quantitatively (This is the place for literature review).

2. Literature Review

The group should locate at 3-5
articles that present quantitative research on the topic selected.

At the end of this section,
the Research Question or Research Hypothesis should be formally stated (Please
do not use articles published before 2000).

3. What is the group’s Research Question or
Research Hypothesis?

Some points
for RQ and Hypothesis

There are basically two kinds of research questions: testable and
non-testable. Neither is better than the other, and both have a place in
applied research.

Examples of non-testable questions are:

How do managers feel about the reorganization?

What do residents feel are the most important problems
facing the community?

Respondents’ answers to these questions could be summarized in
descriptive tables and the results might be extremely valuable to
administrators and planners. Business and social science researchers often ask
non-testable research questions. The shortcoming with these types of questions
is that they do not provide objective cut-off points for decision-makers.

In order to overcome this problem, researchers often seek to answer one
or more testable research questions. Nearly all testable research questions
begin with one of the following two phrases:

Is there a significant difference between …?

Is there a significant relationship between …?

For example:

Is there a significant relationship between the age of
managers

and their attitudes towards the reorganization?

Is there a significant difference between white and
minority residents

with respect to what they feel are the most important
problems

facing the community?

A research hypothesis is a testable statement of opinion. It is created
from the research question by replacing the words “Is there”
with the words “There is,” and also replacing the question
mark with a period. The hypotheses for the two sample research questions would
be:

There is a significant relationship between the age of
managers

and their attitudes towards the reorganization.

There is a significant difference between white and
minority residents

with respect to what they feel are the most important
problems facing the community.

It is not possible to test a hypothesis directly. Instead, you must
turn the hypothesis into a null hypothesis. The null hypothesis is created from
the hypothesis by adding the words “no” or “not” to the
statement. For example, the null hypotheses for the two examples would be:

There is no significant relationship between the age
of managers

and their attitudes towards the reorganization.

There is no significant difference between white and
minority residents

with respect to what they feel are the most important problems
facing the community.

All statistical testing is done on the null hypothesis…never the
hypothesis. The result of a statistical test will enable you to either: 1)
reject the null hypothesis, or 2) fail to reject the null hypothesis. Never
use the words “accept the null hypothesis.”

Source:
https://statpac.com/manual/index.htm?turl=formulatinghypothesesfromresearchquestions.htm

4. Method

Discuss the Research
Methodology (in general). Describe the variable or variables that are being
analyzed. Identify the statistical test you will select to analyze these data
and explain why you chose this test.
Summarize your statistical alternative hypothesis. This section includes
the following sub-sections:

4-1. Describe the Dataset

Example

The primary source of data will be HOPSITAL COMPRE MEDICARE DATA (Add
citation). This dataset provides information on hospital characteristics, such
as: Number of staffed beds, ownership, system membership, staffing by nurses
and non clinical staff, teaching status, percentage of discharge for Medicare
and Medicaid patients, and information regarding the availability of specialty
and high-tech services, as well as Electronic Medical Record (EMR) use
(Describe dataset in 2-3 lines, Google the dataset and find the related website
to find more information about the data).

Also describe the sample size; for example, “we are using Medicare
data-2013, this data includes 3000 obs. for all of the hospitals in the US.”

4-2.
Describe Variables

Next, review the database you
selected and select a variable or variables that are a “best-fit.” That is, choose a variable that
quantitatively measures the concept or concepts articulated in your research
question or hypothesis.

Return to your previously
stated Research Question or Hypothesis and evaluate and report variables you
have selected. (See Table 1 as an example).

Table 1. List of variables used for the analysis

Variable	Definition	Description of code	Source	Year
Total Hospital Beds	Total facility beds set up and staffed at the end of reporting period	Numeric	Medicare Data	2013
….
…..

Source: AHA, 2013

4-3. Describe the Research Method for
Analysis

First,
describe the research method as a general (e.g., this is a quantitative method
and then explain about this method in about one paragraph. If you have this
part in the introduction, you do not need to add here).

Then,
explain the statistical method you plan to use for your analysis (Refer to
content in week 3 on Biostatistics for information on various statistical
methods you can choose from), e.g.:

Example:

Hypothesis: AZ hospitals are more likely to have lower
readmission rates for PN compared to CA.

Research Method:To determine
whether Arizona hospitals are more likely to have lower readmission rate than California, we will use at-test, to determine whether differences across
hospital types are statistically significant (You can
change the test depends on your analysis).

4-4. Describe
statistical
package

Finally,
add one paragraph (2-3 lines) for the statistical package, e.g., Excel or Rstudio.

5. Results

Before doing any
analysis, look at the distribution of selected variables. If there are any outliers,
think about that (you may want to eliminate that). Most of you are using
Rstudio, so look at the density curve for your variable to see the outliers ,
If you have any difficulties working with Rstudio, please send me an email
including the variables in the Excel file and I will send you the codes to run
Rstudio.

Add at least one paragraph and explain:

? Why you needed to see the distribution of data before any
analysis (e.g., check for outliers, finding the best fit test; for example, if
the data had not normal distribution, you can’t use the parametric test, etc.,
so just add 1 or 2 sentences).

? Did you eliminate outliers? (Please write 1 or 2 sentence, if
applicable).

? How many observations do you have in your database and how many
for selected variables, report % of
missing, if there are any missing observations.

? When you are finished with this, go for next steps:

1. Present the results of your statistical analysis;
   include any relevant statistical information (summary tables, including N,
   mean, std. dev.).

For this part you could have at least 1-2 tables and
1-2 figures (depending on your variables bar-chart, pi-chart, or scatter-plot)

1. When you have tables and plots ready, think about
   your finding and state the statistical conclusion, before that make sure
   to run a statistical test (depends on # of groups you may like to use
   ttest or chi-sq or Anova) Do the results present evidence in favor or the
   null hypothesis or evidence that contradicts the null hypothesis?

6. Conclusion and Discussion

? Review your research
questions or hypothesis. How has your
analysis informed this question or hypothesis? Present your conclusion(s) from the results
(presented above) and discuss the meaning of this conclusion(s) considering the
research question or hypothesis presented in your introduction.

? Discuss the results of your
statistical analysis considering the background information presented in the introduction you
need to find at least one paper to support your findings.

? At
the end of this section, add one or two sentences anddiscuss the
limitations associated with this analysis and any other statements you think
are important in understanding the results of this analysis.

List of References

Include a reference page
listing the bibliographic information for all sources cited in this report.
This information should be consistent with requirements specified in the
American Psychological Association (APA) format and style guide.

Please look at the link for
header, page setup, etc.
http://www.apastyle.org/manual/related/sample-experiment-paper-1.pdf).

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