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