The Signature Assignment includes three parts. In Part 1, you will
demonstrate your knowledge of statistical analyses discussed in both
courses. Furthermore, you will provide examples of when is appropriate
to use each one of them. In Parts 2 and 3, you are provided with two
scenarios where you have to discuss your designs and answer each of
the questions provided in each scenario.
Part 1:
Listed below are various statistical analyses from EDR-8201 and
EDR-8202. Briefly describe one way you could use each of the analyses
in a research setting.
● Simple linear regression
● Multiple regression
● Factorial analysis of variance
● Multivariate analysis of variance
● Factor analysis
Assume that you are conducting one of the statistical analyses
mentioned above, and you must decide between using a one- or
two-tailed test. When will be appropriate to use a one-tailed test? When
will be appropriate to use a two-tailed test?
Part 2:
With the current flourishing use of technology in education, a school
district wants to conduct a study to determine which high-tech,
student-centered instructional method would be more successful in
preparing students to take standardized tests in the district. You are
hired as a statistician for the district to help them elucidate this issue.
As the statistician, you are investigating the longitudinal effects (one
academic year) of different high-tech, student-centered instructional
methods on the results of standardized mathematical tests. You have
four groups; each one will be using a different high-tech,
student-centered instructional method approach (inquiry-based learning,
expeditionary learning, personalized learning, and game-based
learning).
Describe the data analysis plan for this project, and be sure to address
the following in your response:
1. Define your independent and dependent variables and your design
2. What is your research hypothesis (hypotheses) and the
corresponding null hypothesis (hypotheses)?
3. Which statistical methods or tests do you plan to use to describe
your data and test your hypothesis? Briefly explain the purpose for
including each of the methods or tests in your analysis.
4. What are the assumptions for the statistical test of your
hypotheses? How will you determine if those assumptions are
reasonable for your data?
5. What descriptive or follow-up (post hoc) tests do you anticipate
may be needed?
6. Assume that your data analysis supports your primary research
hypothesis. Write one or two paragraphs that describe the results
of the statistical tests of the hypotheses (i.e., just the results related
to the anticipated main finding).
Part 3:
Assume you are an educational researcher who wants to investigate the
effects of socioeconomic status (SES), home environment, and school
and neighborhood environment on the academic achievement of middle
school students. You designed a survey to collect the necessary
demographic (SES, home environment, neighborhood environment) data
to match it with their standardized test results.
Your survey is divided into three sections. Section 1 includes SES
information: parent’s education, employment status (currently employed:
yes or no), income level, and receiving free or reduced lunch at school.
In Section 2, the questions are regarding the environment at home, time
spent watching TV (or playing video games) at home, having a TV in
their rooms, computer available to do assignments at home, Internet
access at home, etc. Finally, Section 3 includes questions related to the
safety of the neighborhood environment; some examples include if the
students walk to school, how safe they feel while walking to and from
school, do they feel safe at school, are there a lot of fights at school, etc.
The purpose of collecting these data was to develop a model that can
help to predict academic achievement in middle school children using
some of these variables.
1. There are many variables collected in these data. Your first task is
to discuss some of the considerations that you must make to
determine which variables could or should be included in the
model. Be sure to discuss the concept of multicollinearity.
2. How could you measure for multicollinearity? How could you
address multicollinearity?
3. If you decide to eliminate several of the independent variables, in
order to reduce the number, how should you determine which
variables are more important than others to include in the model?
4. Assume that the end result included five variables that were
significant predictors of academic achievement. Write the
estimated regression equation for the model with all five variables.
Length: Complete responses to all questions and prompts in all three
parts.
References: No references are required, though any sources used other
than those provided within the assignment should be cited and
referenced in APA format
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