Experimental and Quasi-Experimental Designs

Experimental and Quasi-Experimental Designs

Consider an organization that offers a leadership development program for midcareer sales managers. Its marketing collateral states that sales managers and their units are 80% more productive after completion of the program and includes a testimonial of one sales manager whose department sales rose 90% after completion. Underneath the testimonial, they conspicuously position a caption indicating, "Results may vary." Consider how to design an experiment to determine the actual typical results of a particular leadership development program for sales managers. How would you select participants for your study? Would selection be by geographic location, industry, or size of sales force? Should there be random selection?

This week you will explore experimental and quasi-experimental designs and consider threats to their validity. As you review this week's readings, think about how the experimental designs presented might inform your own Doctoral Study as well as how alternative approaches such as content analysis may complement your quantitative findings.

Designing Experiments

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.