While it is important to master the use of SPSS software to conduct data analysis, it is equally important to ensure quality in the methods used to collect the data analyzed.

While it is important to master the use of SPSS software to conduct data analysis, it is equally important to ensure quality in the methods used to collect the data analyzed. Recall the familiar adage, “Garbage in, garbage out,” and consider that if data is poorly collected, the analysis of that data will also suffer. Think about how the interrelatedness of the hypothesis, data collection method, and statistical analysis impacts research quality.

Having reviewed the readings from Experimental and Quasi-Experimental Designs for Research, by Campbell and Stanley, consider the hypothesis you have chosen for your dataset from Week 3. How might you design an experiment that will effectively collect data for this chosen hypothesis? How will you minimize threats to validity? Will it be a true experiment or a quasi-experiment? Why or why not?

With these thoughts in mind:

Compose an experiment design for the hypothesis you selected for your chosen dataset. In your response, address all the factors that potentially jeopardize the validity of your design. Describe the methods, variables, and measures of control as well as the corresponding research statistics that will be employed. Address each design component in 1–2 separate paragraphs.

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