Designing Experiments:
Paper details:
Discussion: Designin" rel="nofollow">ing Experiments
While it is important to master the use of SPSS software to conduct data analysis, it is equally important to ensure
quality in" rel="nofollow">in the methods used to collect the data analyzed. Recall the familiar adage, "Garbage in" rel="nofollow">in, garbage out," and
consider that if data is poorly collected, the analysis of that data will also suffer. Thin" rel="nofollow">ink about how the
in" rel="nofollow">interrelatedness of the hypothesis, data collection method, and statistical analysis impacts research quality.
Havin" rel="nofollow">ing reviewed the readin" rel="nofollow">ings from Experimental and QuasiExperimental Designs for Research, by Campbell and
Stanley, consider the hypothesis you have chosen for yoÕÉ≠†Њ†ur dataset from Week 3. How might you design
an experiment that will effectively collect data for this chosen hypothesis? How will you min" rel="nofollow">inimize threats to validity?
Will it be a true experiment or a quasiexperiment? Why or why not?
With these thoughts in" rel="nofollow">in min" rel="nofollow">ind:
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 correspondin" rel="nofollow">ing research statistics that will be employed. Address each design
component in" rel="nofollow">in 1–2 separate paragraphs.