Quasi-Experimental and Experimental Designs Data tutorial

This is a paper that is focusing on the Quasi-Experimental and Experimental Designs Data tutorial. The paper also provides additional information to use in writing the assignment paper.

Quasi-Experimental and Experimental Designs Data tutorial

Assignment: Prepare a Tutorial on Presenting Quasi-Experimental and Experimental Designs Data

Instructions
A tutorial is a step-by-step guide with logical steps in which attention to detail is paramount. A tutorial is a set of instructions that guides a reader and the result is that the reader now knows how to do something that they did not know how to do before.
For this task, you will prepare a tutorial on quasi-experimental and experimental designs. Your tutorial will serve as a step by step guide as to how you would use statistical analysis in both designs.
Support your tutorial with at least 5 references from scholarly sources.
Length: 5pages
Your tutorial should demonstrate thoughtful consideration of the ideas and concepts presented in the course by providing new thoughts and insights relating directly to the topic. Your response should reflect scholarly writing and current APA standards.

Data Presentation for Both Designs
Once a researcher has determined which design will be used and the experiment to be conducted, the next step is presenting the data collected. Presenting the data can take several forms that include graphs, charts, and tables. When presenting data, the researcher displays the data and also justifies why a particular design is used. For example, presenting data for an experimental design could be in the form of a table reflecting the results of an Independent Sample t test (please review the APA manual). For a quasi-experimental design, a researcher might use a graph to represent and illustrate the data.
When presenting study results researchers develop graphs, tables, other visual displays that reflect the results of the analysis. Data presentation for both these designs can be by interpreting t tests and graphing the means. As well as determining the effect size.