2Discussions.docx

Discussion 1

Choose one and discuss in detail:

1. Be able to design research given a scenario. For example: You decide to study the effects of distracted driving on attention. Design the study. Two groups? More than two? Repeated measures? Counterbalancing? Factorial? Identify IV's, DV's, CV's. State the hypothesis/purpose. Give a complete rationale, explanation.

2. List and define the nine steps in designing a survey research project (page 294).

3. Define the types of sampling

4. Define and Discuss validity and reliability

5. Be able to determine number of IV's, DV's, levels, factors, and number of groups in factorial designs (example: 2×4 design has two IV's, one DV, two levels of first IV, 4 levels of second IV, and 8 groups – also 80 subjects if 10 per group).

6. Be able to identify IV's, DV's and come up with potential control variables (extraneous variables) that need to be controlled in any given study.

Example:

Researchers are interested in whether or not Incontinence in the elderly can be cured without drugs.

Answer:

IV would be various non-medical intervention treatments, DV is amount or degree of incontinence – maybe weigh the depends diapers every two hours, confounds might be age – so maybe match subjects or use age as another IV, gender also because males and females may differ in degree of incontinence at same ages, availability of bathroom facilities (if in a nursing home it may be down the hall, while in home care it may be a private bath off the bedroom, or some places may have better nursing care than other places).

Discussion 2

Here's the list of topics for this last discussion of the semester!

· Report the percentages of the bell curve as cut-off by standard deviations (and standard errors – both are the same percentages) and how they relate to p < .05 and p < .01.

· Define when to use which statistical test and provide an example of each (z-score analysis, independent groups t-test, repeated measures t-test, analysis of variance).

· Describe Type I and II errors in statistical decisions, and provide examples.