Solution Design either a quasi or experimental study to investigate

Design either a quasi or experimental study to investigate the variables. What is the hypothesis? Describe the types of hypotheses with respect to testing. What does the experimental method allow that the correlation design does not?

Each CLC team will design a quasi or a true experimental study, investigating the impact of the independent variable on the dependent variable.

Address the following in 500-750 words:

Design either a quasi or experimental study to investigate the variables. What is the hypothesis?

Describe the types of hypotheses with respect to testing. What does the experimental method allow that the correlation design does not?

Identify the independent variable. Identify the dependent variable.

Describe how the group will define operationally and measure the variables.

Describe how the group will obtain a random sample of participants.

Discuss how the group will ensure the study has high internal validity. Will the subjects be assigned randomly to the groups? Why or why not.

Are there any ethical concerns about the treatment of participants emerging from the experiment?
Consider the data presented, would you use t or F score? Why? include the appropriate effect size.
Submit an SPSS output for the quasi or true experimental study.
Include at least two to four scholarly sources.

While APA style is not required for the body of this assignment, solid academic writing is expected and in-text citations and references should be presented using APA documentation guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

Quasi-experimental research types

There are many different sorts of quasi-experimental designs. Three of the most popular varieties are described below: Design of non-equivalent groups, Discontinuity in regression, and Natural experiments.

• Design of Non-equivalent GroupsThe researcher picks existing groups that look comparable, but only one of the groups receives the therapy in a non-equivalent group design.
  
  When employing this design, researchers attempt to accommodate for any confounding factors by adjusting for them in their study or selecting groups that are as comparable as feasible. The most prevalent sort of quasi-experimental design is this one.
  
  Example: Design of Non-equivalent GroupsYou believe that the new after-school activity will result in improved academic performance. You pick two comparable groups of students from separate classes, one of which uses the new program and the other does not.
  
  You can see if the program influences grades by comparing students who participate to those who do not.
• Discontinuity in regressionMany of the prospective therapies that researchers want to investigate are based on a basic arbitrary cutoff, with those who fall over the threshold receiving treatment and those who fall below it not. At this point, the group differences are frequently so minor that they are almost non-existent.
  
  As a result, researchers can utilize people who are under the limit as a reference group and people who are just beyond it as an intervention group.
  
  Example: Discontinuity in regressionIn the United States, certain high schools are reserved for pupils who achieve a specified level of achievement on a test. Those who succeed in this exam are likely to vary from those who do not in a systematic way.
  
  However, because the precise cutoff number is arbitrary, students near the limit who barely pass exams and those who fail by a razor-thin margin tend to be extremely similar, with the minute variations in their results owing primarily to chance. As a result, any disparities in outcomes must be due to their educational experiences.
  
  You may look at the long-term outcomes of these two groups of kids to see how attending a selective school affects them.
• Natural experimentsResearchers usually choose which group the individuals are allocated to in both lab and outdoor tests. A random or irregular assignment of patients to the control treatment occurs in a natural experiment because of an external occurrence or scenario (“nature”).
  
  Natural experiments are not actual experiments since they are observational, even though some employ random assignments.
  
  Example: Natural experimentsOne of the best-known natural experiments is the Oregon Health Study. In 2008, Oregon voted to increase the number of low-income people enrolled in Medicaid, America’s low-income public health care program.

However, because they couldn’t afford to pay everyone who qualified for the program, they had to use a random lottery to distribute slots.

Experts were able to investigate the program’s impact by utilizing enrolled people as a treatment group and those who were qualified but did not play the jackpot as an experimental group.

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