Data Analysis Project Overview: In this summative assessment, you will use the College Student Survey dataset to be the basis for your report. In addition to the demographic variables surveyed (e.g. age, sex/gender, ethnicity, race, etc.), you will choose 2 measured variables from this list (GRIT, mindset, academic procrastination, academic self-efficacy, self-regulated learning, impostor phenomenon, and academic burnout) to evaluate for your report. You will apply the statistical analysis skills and interpretation skills to explain the data and write up a report of the results. You will be evaluated not only on your computations but also on your explanation of the interpretation of the data.
Final Data Analysis Report Overview: You will demonstrate skills in discipline-specific professional communication and integration of everything you have learned throughout the semester. Thus, your 3rd assignment will be to produce a final Data Analysis Report. Your report should be an APA styled and formatted Microsoft Word document that will be approximately 8-12 pages long. It will include the following sections: introduction, method, results, discussion, and references. It will have a title page and incorporate appropriate tables and figures. You will have the opportunity to submit drafts (milestones) of these sections for peer review and feedback throughout the semester. You will describe the research question of interest in the introduction and include relevant support from the literature. You should also formulate at least 1 specific hypothesis regarding your research question. In the method section, you will provide information regarding the participants, materials and procedures utilized to collect data. In the results section, you will use statistical software to complete data analysis on your chosen data to test your hypothesis to answer your research question. In the discussion section, you will summarize your results and discuss the real-world implications of the results and further research on the topic. You will need to include at least 5 peer-reviewed sources in your final report.
Final Data Analysis Report Checklist (these are the elements that must be included in order to have a complete submission)
Title Page: Report title, Name, Affiliation
Introduction: Research Question and Research Hypotheses
Introduction: Variable Choice and Background Summary
Introduction: Ethical Issues
Introduction: Ensure Alignment
Method: Sample Size
Method: Instruments
Method: Statistical Procedures
Results: Descriptive – Mean and Standard Deviation
Results: Descriptive – Tables
Results: Descriptive – Figures
Results: Descriptive – Shape
Results: Inferential – Group Comparisons: Null and Alternative Hypotheses
Results: Inferential – Group Comparisons: Whether One Mean is Higher
Results: Inferential – Predictions: Null and Alternative Hypotheses
Results: Statistically Significant
Results: Valid
Results: Inferential Figure(s)
Discussion: Interpretation
Discussion: Data Analysis Procedures
Discussion: More Statistical Procedures
Discussion: Potential Implications and Future Research
References Page: References
APA Style and Formatting
Final Data Analysis Report Rubric
Guidelines
for Submission: Your
report should be approximately 6 to 8 pages (not including cover page,
references) and must be written in APA format. Use double spacing, one-inch
margins, and 12-point Times New Roman font. Include a cover page for your
report, you do not need an abstract. Include at least five references, cited in
APA format.
Critical
Elements
Exemplary
(100%)
Proficient
(85%)
Needs
Improvement (55%)
Not
Evident (0%)
Introduction:
Research
Question and Research Hypotheses
Meets
“Proficient” criteria and the connections between the research questions and
research hypotheses are exceptionally clear
States
the research questions and related research hypotheses that will be evaluated
using the chosen data
States
research questions and related research hypothesis, but there are
inaccuracies or they are illogical
Does
not state research questions and related research hypotheses
Introduction:
Variable Choice and Background Summary
Meets
“Proficient” criteria and explanations are exceptionally clear and
contextualized around the research questions being addressed and the
background used to justify the hypotheses
Indicates
variable choice and explains why this particular variable focus is important.
Provides an accurate summary of previous investigations of the chosen
variables by incorporating examples from findings published in peer-reviewed
sources.
Provides
a summary of the variables chosen, but summary is cursory or illogical
Does
not summarize the variables chosen
Introduction:
Ethical Issues
Meets
“Proficient” criteria and draws insightful connections between ethical issues
and data
analysis
and reporting
Discusses
ethical issues that may potentially arise when analyzing and reporting
statistical data
Discusses
ethical issues that may potentially arise when analyzing and reporting
statistical data, but
discussion
is cursory or illogical
Does
not discuss ethical issues that may potentially arise when analyzing and
reporting statistical
data
Introduction:
Ensure Alignment
Meets
“Proficient” criteria and demonstrates a nuanced understanding of ethical
data analysis and reporting
Explains
what will be done in personal data analysis and reporting to ensure alignment
with the expectations of the APA Ethical Principles of Psychologists
Explains
what will be done in personal data analysis and reporting to ensure alignment
with the expectations of the APA Ethical Principles of Psychologists, but
explanation is
illogical
or irrelevant
Does
not explain what will be done in personal data analysis and reporting to
ensure alignment with the expectations of the APA Ethical Principles of
Psychologists
Method:
Sample
Size
Meets
“Proficient” criteria and explanation demonstrates a sophisticated awareness
of how the sample size can inform
statistical
analysis
Identifies
the sample size and explains how the sample size will inform the statistical
analysis
Identifies
the sample size and explains how the sample size will inform the statistical
analysis but explanation is cursory or contains
inaccuracies
Does
not identify the sample size or explain how the sample size will inform the
statistical analysis
Method:
Instruments
Meets
“Proficient criteria” and demonstrates a nuanced understanding of the
structure of the assessments/scales used to measure the variables of interest
Describes
the assessment/scales used to measure the variables of interest while
including example items and explanation of how scores are computed
Describes
the assessment/scales used to measure the variables of interest but
description is cursory and/or incomplete
Does
not provide description of the assessment/scales used to measure the
variables of interest
Method:
Statistical
Procedures
Meets
“Proficient” criteria and demonstrates a nuanced understanding of appropriate
application of statistical procedures
Selects
what procedures should be implemented in the analysis and justifies why these
statistical procedures are appropriate
Selects
what procedures should be implemented in the analysis and justifies why these
statistical procedures are appropriate, but some procedures selected are not
appropriate or the
justification
is not logical
Does
not select what procedures should be implemented in the analysis and justify
why these statistical procedures are appropriate
Results:
Descriptive
Mean
and Standard Deviation
Computes
the mean and standard deviation accurately for each set of scores using
appropriate abbreviations and terminology
Computes
the mean and standard deviation for each set of scores, but computations are
not accurate or do not use appropriate abbreviations and
terminology
Does
not compute the mean and standard deviation for each set of scores
Results:
Descriptive
Tables
Prepares
an accurate, appropriately labeled table which includes summary values for
demographic variables
Prepares
a table for demographic variables, but the table includes inaccurate values
or is not properly labeled
Does
not prepare a table for demographic variables
Results:
Descriptive Figures
Prepares
an accurate, appropriately labeled histogram graph for each set of scores or
score distribution.
Prepares
a histogram graph for each set of scores or score distribution, but the
graphs are not accurate or are not
appropriately
labeled
Does
not prepare a histogram graph for each set of scores or score distribution
Results:
Descriptive
Shape
Meets “Proficient”
criteria and evaluation demonstrates keen insight into what the shape of a
distribution
says about the data
Evaluates
the shape of each distribution using created histograms
Evaluates
the shape of each distribution using created histograms, but evaluation is
cursory
or contains inaccuracies
Does
not evaluate the shape of each distribution using created histograms
Results:
Inferential
Group
comparisons
Null
Hypothesis and Alternative Hypothesis
Accurately
identifies the null hypothesis and alternative hypothesis in language based
on what is being compared and using appropriate statistical
symbols
Identifies
the null hypothesis and alternative hypothesis in language based on what is
being compared, but identification is not accurate/does not use
appropriate
statistic symbols
Does
not identify the null hypothesis and alternative hypothesis
Results:
Inferential
Group
comparisons Whether One Mean is Higher
Accurately
determines whether one mean is higher, showing how the determination was made
Determines
whether one mean is higher, but result is inaccurate or does not show how the
determination
was made
Does
not determine whether one mean is higher
Results:
Inferential
Predictions
Null
Hypothesis and Alternative Hypothesis
Accurately
identifies the null hypothesis and alternative hypothesis in language based
on the measured variables being compared and using appropriate statistical
symbols
Identifies
the null hypothesis and alternative hypothesis in language based on the
measured variables being compared, but identification is not accurate/does
not use
appropriate
statistic symbols
Does
not identify the null hypothesis and alternative hypothesis
Results:
Statistically Significant
Meets
“Proficient” criteria and explanation is exceptionally clear and
contextualized
Explains
whether or not the results are statistically significant
Explains
whether or not the results are statistically significant, but explanation is
cursory or
Illogical
Does
not explain whether or not the results are statistically significant
Results:
Valid
Accurately
determines if the data provides evidence for a valid effect
Determines
if the data provides evidence for a valid effect, but the determination is
illogical or
Inaccurate
Does
not determine if the data provides evidence for a valid effect
Results:
Inferential
Figure(s)
Meets
“Proficient” criteria and graphs are exceptionally well developed and
readable
Presents
accurate, properly labeled graphs representing the data analysis results
detailed clearly for ease of stakeholder
interpretation
Presents
graphs representing the data analysis results, but the graphs are inaccurate,
improperly labeled, or are lacking
in
detail
Does
not present graphs representing the data analysis results
Discussion:
Interpretation
Meets
“Proficient” criteria and uses discipline-specific terminology to establish
expertise without overwhelming
stakeholders
Explains
the interpretation of the data
Explains
the interpretation of the data, but explanation is cursory or illogical
Does
not explain the interpretation of the data
Discussion:
Data Analysis Procedures
Meets
“Proficient” criteria and demonstrates a deep understanding of ethical data
analysis procedures
Justifies
the data analysis procedures used to reach the interpretation
Justifies
the data analysis procedures used to reach the interpretation, but
justification is
illogical
Does
not justify the data analysis procedures used to reach the interpretation
Discussion:
More Statistical Procedures
Meets
“Proficient” criteria and discussion is exceptionally clear and
contextualized
Discusses
whether it would be appropriate to conduct more statistical procedures to
further interpret the data
Discusses
whether it would be appropriate to conduct more statistical procedures to
further interpret the data, but discussion is cursory or contains issues of
clarity
Does
not discuss whether it would be appropriate to conduct more statistical
procedures to further interpret the data
Discussion:
Implications and Future Research
Meets
“Proficient” criteria and discussion is exceptionally clear and
contextualized
Discusses
the potential implications for the results and one idea for a future
direction for research topic
Discusses
potential implications and future directions, but discussion is cursory or
illogical
Does
not discuss implications and future direction for research
Articulation
of Response
Submission
is free of errors related to citations, grammar, spelling, syntax, and
organization and is presented in a professional and easy to read format
Submission
has no major errors related to citations, grammar, spelling, syntax, or
organization
Submission
has major errors related to citations, grammar, spelling, syntax, or
organization that negatively impact readability and articulation of main
ideas
Submission
has critical errors related to citations, grammar, spelling, syntax, or
organization that prevent understanding of ideas

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