IBM SPSS Analyses; A univariate analysis

  

ANSWER MUST INCLUDE SPPS output file….Using this data, perform a univariate analysis of your choice on the
variables provided. Your analysis may be a t test, an ANOVA, a
correlation, a linear or multiple regression, or a non-parametric method. For
example, you may want to use gender as an independent variable, and quiz one
scores as a dependent variable and perform an independent samples t
test. Or, as another example, we might have ethnicity as our independent
variable, and run a one way ANOVA with GPA as the dependent measure.
Be creative, but be sure your variables are correct for the analysis you are
doing.
Follow the Data Analysis Formatting
Guidelines items to give clarity and organization to your assignment.
You must include an introduction and rationale for your analysis, your null
and alternative hypotheses, your alpha level, descriptive statistics, output
tables, and conclusions about the null. All tables and graphs must be properly
labeled, and each must be discussed and interpreted in the paper. Do not just
copy and paste tables or graphs into the assignment. You must show your
understanding of the hypothesis testing method, as well as your understanding
of what you are doing.
Write in third person, using a clear and professional tone, voice and style.
Use proper APA citations and references as needed. Data Analysis Formatting Guidelines
The format and organization of this model should be used for
all subsequent data analysis assignments. See the Instructor’s Expectations in
the course syllabus for additional details. Note that all tables and figures
are clearly and appropriately identified. Clarity of writing and following
instructions are gradable components of all assignments.
Section I – Data File Description
The
source of the database.Any
history or “story” that provides context for the data.All
variable(s) that are used in the analysis, including the measurement scale
associated with each variable and any missing cases.The
number of cases (sample size).The
presumed population.Any
other general information that describes the data file and variables.
Section II – Assumptions, Data
Screening, and Verification of Assumptions
Clearly
identify and verify any assumptions and requirements underlying the use of
each inferential statistical procedure. Systematically
verify each assumption and requirement for the variables that will be used
in the analysis.If
an assumption or requirement cannot be verified with the given
information, indicate what information would be needed to provide
verification.If
the assumption or requirement is not consistent with the variables in the
data file, indicate what remediation might be undertaken to ameliorate the
problem.Screen
the data for out-of-bound values and outliers.
Section III – Inferential Procedure,
Hypotheses, Alpha Level
State
the alpha level (use .05 unless otherwise indicated).State
the research question(s).State
the statistical hypotheses, both null and alternative.Indicate
what the calculated statistic will be that addresses each of the
hypotheses.
Section IV – Interpretation
Indicate
the results and interpret the meaning of the results for each inferential
analysis and do this specifically for the variables that are being
analyzed.State
your conclusions, as they relate directly to the research questions and
hypotheses, based on the interpretation of the results.Indicate
any limitations or constraints regarding these conclusions.
….ATTACHED zip file contains the assignment in MS Word Format and the required SPSS grades.sav….
w2_assignment_basic_ibm_spss_analyses.docx

week2.assignement.spss.datafile.zip

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IBM SPSS Analyses; A univariate analysis
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Assignment 1 – Basic IBM SPSS Analyses
In this first assignment, you will use the data from the grades.sav.
Using this data, perform a univariate analysis of your choice on the variables provided. Your analysis
may be a t test, an ANOVA, a correlation, a linear or multiple regression, or a non-parametric method.
For example, you may want to use gender as an independent variable, and quiz one scores as a
dependent variable and perform an independent samples t test. Or, as another example, we might have
ethnicity as our independent variable, and run a one way ANOVA with GPA as the dependent measure.
Be creative, but be sure your variables are correct for the analysis you are doing.
Follow the Data Analysis Formatting Guidelines items to give clarity and organization to your
assignment.
You must include an introduction and rationale for your analysis, your null and alternative hypotheses,
your alpha level, descriptive statistics, output tables, and conclusions about the null. All tables and
graphs must be properly labeled, and each must be discussed and interpreted in the paper. Do not just
copy and paste tables or graphs into the assignment. You must show your understanding of the
hypothesis testing method, as well as your understanding of what you are doing.
Write in third person, using a clear and professional tone, voice and style. Use proper APA citations and
references as needed.
Xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Data Analysis Formatting Guidelines
The format and organization of this model should be used for all subsequent data analysis assignments.
See the Instructor’s Expectations in the course syllabus for additional details. Note that all tables and
figures are clearly and appropriately identified. Clarity of writing and following instructions are gradable
components of all assignments.
Section I – Data File Description






The source of the database.
Any history or “story” that provides context for the data.
All variable(s) that are used in the analysis, including the measurement scale associated with
each variable and any missing cases.
The number of cases (sample size).
The presumed population.
Any other general information that describes the data file and variables.
Section II – Assumptions, Data Screening, and Verification of Assumptions


Clearly identify and verify any assumptions and requirements underlying the use of each
inferential statistical procedure.
Systematically verify each assumption and requirement for the variables that will be used in the
analysis.



If an assumption or requirement cannot be verified with the given information, indicate what
information would be needed to provide verification.
If the assumption or requirement is not consistent with the variables in the data file, indicate
what remediation might be undertaken to ameliorate the problem.
Screen the data for out-of-bound values and outliers.
Section III – Inferential Procedure, Hypotheses, Alpha Level




State the alpha level (use .05 unless otherwise indicated).
State the research question(s).
State the statistical hypotheses, both null and alternative.
Indicate what the calculated statistic will be that addresses each of the hypotheses.
Section IV – Interpretation



Indicate the results and interpret the meaning of the results for each inferential analysis and do
this specifically for the variables that are being analyzed.
State your conclusions, as they relate directly to the research questions and hypotheses, based on
the interpretation of the results.
Indicate any limitations or constraints regarding these conclusions.
Xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

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