You must use the concepts you learn in this course throughout the rest of your program. To help you do this, you will build a couple of tools to help you during and after you finish this course. The first is a table of what statistical tests can be used when you have independent (or predictor) variables (IV) and dependent (or outcome) variables (DV) with various levels of measurement. The second is an analysis/critique checklist of things you should consider when performing an analysis or critiquing the statistical analyses used in a research report. You must add information to your copy of these tools and turn it in each week as we go through the course.

Which statistical test should I use?

| | | Independent
(or Predictor)
Variable (IV)
| | | | | :---: | :---: | :---: | :---: | :---: | :---: | |


| | Nominal | Ordinal | Interval | Ratio | | Dependent
(or Outcome)
Variable (DV)

| Nominal | | | | | |


| Ordinal | | | | | |


| Interval | | | | | |


| Ratio | | | | |

Statistical Analysis/Critique Steps

Hopefully, the statistics you calculate are more than just a collection of random facts about the data you have. Most of the time, individuals and organizations seek to answer a question or solve a problem using statistical data. As such, the statistics you calculate should be part of the supporting evidence of a well-crafted argument (Booth et al., 2016). Validity is an overarching concern of science and refers to the level of truth we ascribe to inferences (Shadish et al., 2002). This checklist aims to help you gather information relevant to establishing the validity of the inferences you seek to make with the statistics you calculate. The answers you provide to the prompts in this checklist are the logical foundation upon which any arguments you desire to make with the results of your analyses rest. Ensuring the integrity of your data and analyses is part of ethical statistical practice (American Statistical Association, 2022). Background information should not be overlooked when conducting and interpreting statistical analyses. It’s never a bad idea to consult a statistician during the planning stages of a study or analysis to ensure the data collection and analysis plan is sound (Berman & Gullion, 2007). This checklist will also help you gather and prepare the information needed to work with a statistician or critique the work of others.

| Analysis/Critique Checklist | | --- | | | | --------------------Section #1: Study Information (The Big Picture)-------------------- | | | | $\textcolor{red}{Add \ this \ section:}$ What are the research questions for this study? Have the investigators hypothesized any outcomes? | |



| | --------------------Section #2: Dataset Information (Data Screening & Data Cleaning)-------------------- | | | | $\textcolor{red}{Add \ this \ section:}$ What are the variables in the dataset and the level of measurement for each one? | |



| | --------------------Section #3: Individual Test Information (Complete this section for each test run.)-------------------- | | | | $\textcolor{red}{Add \ this \ section:}$ What are the independent (or predictor) and dependent (or outcome) variables for the test, and what is the level of measurement for each one? | |



| | --------------------References-------------------- | | American Statistical Association. (2022, February 1, 2022). Ethical guidelines for statistical practice. Retrieved October 10 from https://www.amstat.org/your-career/ethical-guidelines-for-statistical-practice

Berman, N., & Gullíon, C. (2007). Working with a Statistician. Topics in Biostatistics, 489-503.

Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., & Fitzgerald, W. T. (2016). The craft of research (Fourth ed.). University of Chicago Press. https://doi.org/10.7208/chicago/9780226239873.001.0001

Field, A. (2018). Discovering statistics using IBM SPSS statistics (Fifth ed.). SAGE Publications, Inc.

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Wadsworth, Cengage Learning.

Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (Seventh ed.). Pearson Education, Inc. |