RES/720 Statistical Research Methods and Design II sample papers, week by week

Reviewed by Davina Cresswell, MBA · Statistical Research Methods and Design II · University of Phoenix · Free custom samples in 24–48h

RES/720 extends doctoral statistics to advanced procedures. Eight weekly samples cover design choice, one-way ANOVA, factorial ANOVA, multiple regression, logistic regression, chi-square and nonparametric tests, interpretation and a quantitative analysis plan.

Send the exact assignment or rubric from your classroom and a custom sample written to it lands in 24 to 48 hours, the first one free. RES/720 is Phoenix’s Statistical Research Methods and Design II course. It expands students' understanding of research methodology through advanced statistical procedures, applying investigative processes to apply, interpret and draw conclusions from complex approaches to quantitative research. Searches like "res/720 week 3 assignment example", "RES720 sample paper", and "RES 720 week samples" land on this page.

What RES/720 is really about

Real problems rarely involve just two groups or two variables. RES/720 covers comparing several groups with ANOVA and post hoc tests, examining interactions in factorial designs, predicting outcomes with multiple and logistic regression, analyzing categories with chi-square and choosing nonparametric tests when assumptions fail.

Students typically match procedures to research questions, run and interpret ANOVA and regression models, test assumptions, analyze categorical data, critique advanced statistics in published studies and write a data analysis plan for a proposed study.

What RES/720’s assessments ask for

Faculty expect correct procedure selection, assumption testing, APA reporting with effect sizes and confidence intervals and interpretation that connects results to the research question. Analysis plans should specify variables, tests and the software used.

Where students lose points in RES/720

Work loses credit when many separate t tests replace an ANOVA, when regression coefficients are interpreted without holding other variables constant or when multicollinearity is ignored. Overstating causal claims from observational data is another frequent error. Name the sample size needed for each planned test and show the power calculation, since underpowered designs are a common reason proposals are sent back.

The RES/720 drawers

Wk 1

RES/720 Wk 1 assignment example

Wk 1 usually introduces advanced design choices. On request, free, 24-48h.

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Wk 2

RES/720 Wk 2 assignment example

Wk 2 typically applies one-way ANOVA. On request, free, 24-48h.

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Wk 3

RES/720 Wk 3 assignment example

Wk 3 often examines factorial ANOVA. On request, free, 24-48h.

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Wk 4

RES/720 Wk 4 assignment example

Wk 4 commonly covers multiple regression. On request, free, 24-48h.

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Wk 5

RES/720 Wk 5 assignment example

Wk 5 usually addresses logistic regression. On request, free, 24-48h.

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Wk 6

RES/720 Wk 6 assignment example

Wk 6 typically applies chi-square and nonparametric tests. On request, free, 24-48h.

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Wk 7

RES/720 Wk 7 assignment example

Wk 7 often interprets complex results. On request, free, 24-48h.

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Wk 8

RES/720 Wk 8 assignment example

Wk 8 closes with a quantitative analysis plan. On request, free, 24-48h.

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University of Phoenix revises courses; week counts and deliverables shift between terms. Send what your classroom shows and the desk matches it exactly.

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Using a RES/720 sample the right way

Share the research question and variables; the free sample picks the procedure and interprets the output.

How these samples are written

Method, in one line: instructions first, structure from the rubric, artifacts exact. Week counts vary by course model; the catch-all row absorbs the difference. Your free request matches what your classroom actually shows.

RES/720 questions, answered

Why use ANOVA instead of several t tests?

Running many t tests inflates the chance of a false positive; ANOVA tests all group means at once.

What is multicollinearity?

High correlation among predictors in a regression, which makes coefficients unstable and hard to interpret.

When is logistic regression used?

When the outcome is categorical, such as yes or no, rather than continuous.