Reference no: EM132639082

If experience is the best teacher, what better way to learn about the totality of case method instruction than by writing a case? Many first-time case authors have, to their pleasant surprise, written wonderful teaching documents-sometimes classics. Beginners, therefore, take heart: however untested your writing abilities, you have a better chance of doing a good job than you may think. In this endeavor, neophytes have a somewhat paradoxical advantage over more experienced colleagues: they think more like readers than writers. ... The interview process gives the researcher unique access to "backstage" information about the story, which, by definition, embodies some principle or way of thinking worth studying. And who but the researcher gets to talk with those who participated in the events, sense their personalities, hear the shadings in their voices, and come as close as anyone can, through conversation, to walking a mile in their moccasins? I compare the process of selecting case data to film editing; many wonderful scenes in case drafts end up sacrificed to brevity or coherence of pattern, on the "cutting room floor," but the researcher-writer sees them all. - Louis B. Barnes

Steps
1. Read through the requirements and instructions.
2. Complete Part 1 (3 multiple choice questions).
3. Complete Part 2 (4 open-ended questions, at least 500 words total).
4. Submit Part 1 and 2 in the RA 2 quiz AND upload Part 2 to turnitin.com in the RA 2: File assignment. You don't need to include Part 1 information in the RA 2: File (just Part 2).
Background Information

Review the lecture information on research methods. Then, you will apply this information to your own research strategy.

Observational vs. Experimental Studies

• ObservationalStudy - A study which observes individuals and measures variables, but does not attempt to influence the responses. An observational study cannot show cause-and-effect relationships because there is the possibility that the response is affected by some variable(s) other than the ones being measured. That is, confounding variables may be present.
• Experiment - A study in which treatment(s) are deliberately imposed on individuals in order to observe their response. An experiment in which the treatments are randomly assigned to individuals can provide evidence for a cause-and-effect relationship. Furthermore, if the individuals are from a random sample, then one can generalize conclusions from the experiment to the population.

To recognize the difference between an Observational Study and an Experiment, ask yourself, "Was there a treatment imposed on the individuals?" In an experiment, the researcher determines (randomly) which individuals receive which treatment. In an observational study, the individuals have already self-chosen their groups. These studies are just documenting observations.

Qualitative vs. Quantitative Data
Qualitative data is non-statistical and uses an open-ended question format. Data is categorized by properties and attributes. Quantitative data is measured numerically and uses a close-ended format (respondents must choose from a list of answer choices). Surveys can be quantitative or qualitative (or incorporate both). Interviews tend to be qualitative in nature but may incorporate some close-ended questions to collect demographic data.
• Open-ended questions
o Ex: Tell me a little about your illness. How has it developed?
• Close-ended questions
o Ex: On a scale of 1-5, how would you rate your satisfaction with this service?
• Structured interview - Questions are prepared in advance and asked to each interviewee in the same order
• Unstructured interview - Interviewer asks open-ended questions on a topic and will let the interview flow like a natural conversation
Variables

• Nominal variables - no quantitative properties; categorical
o Ex: name, occupation, etc.
• Ordinal variables - variables have a natural order or ranking based on magnitude, but the distance between ranks may not be equal
o Ex: questionnaire score on a scale of 1 to 5, income level, education level, etc.
• Interval variables - variables have a ranking based on magnitude, the distance between ranks is equal, and the zero point does not have a natural meaning
o Ex: a pH of 0 does not mean there is an absence of acidity...there is a ranking difference between a pH of 12 and a pH of 4. However, the "0" score has an arbitrary meaning.
• Ratio variables - numerical values; variables have a natural order or ranking based on magnitude, the distance between ranks is equal, and there is an absolute "zero" point
o Ex: height, blood pressure, number of appliances owned, etc.

There are various methods that researchers can use to generate a sample:
• Random - each person has an equal chance of being selected
• Stratified Random - divides population into groups or strata and randomly selects individuals from each group
• Systematic - includes every nth observation of the population in study
• Quota - the assembled sample has the same proportion of individuals as the total population (ex: educational level, income, sex, etc.)
• Cluster - clusters of observations representing the population are identified as the sample population

Let's observe how sampling might influence interpretations of a dataset. Follow along with the video instructions.

Part 1: Sampling Exercise

1. Watch the Excel sampling videos (to be updated). It may be helpful to follow along with the video instructions in your own spreadsheet to practice analyzing a dataset. It is not required to turn in a spreadsheet. This information is meant to help you understand sampling and be able to apply it to your own research.
a. Creating a Dataset in Excel
b. Random Sampling
c. Systematic
d. Quota
e. T-test

Part 1 Questions

1. Are the following observational or experimental studies?
• A study of birth weight of babies and the mother's level of coffee consumption.
• A study of lab mice completing two different types of mazes.
• A study of gender versus salary.
• A study of annual grizzly bear attacks.
• A study of the number of 1's rolled on a weighted die.
2. Which of the variables in this dataset are nominal, ordinal, interval, and ratio (if any)? Think carefully about these variables. Even though different rankings are discussed with some of these variables, think about the data that was actually entered into the spreadsheet for the population of 200.
• Age
• Sex
• Skin Tone Perception
• Grade Level
• Hypersexuality Perceptions
• Dress Code Violations
• Disciplinary Actions
3. Are the p-values for the following results statistically significant?
• p = 0.06132
• p = 0.02179
• p = 1.78231 E-5
• p = 1.78231 E5

Part 2: Your Research
Next, figure out specific aspects of your topic that you want to examine. Create a table to narrow down your topic:

Come up with a central research question (or multiple research questions) you wish to address in your case study. A research question (different from a hypothesis - hypotheses are predictions) is a general question that you are trying to answer in your research.
Which of the following is a better research question?
A. How does sexism affect students?
B. How do racialized perceptions of sexuality impact dress code policies in Bay Area high schools?
B - Question A is too vague and lacks a clear task. Question B, however, consists of clearly defined content, encourages the writer to identify underlying influences, and presents a clear argument.

Part 2 Requirements

Answer the following questions in at least 500 words (total). These responses should be professional (grammatically correct, contains structured sentences, etc.). When answering these questions, include at least 2 additional references (you may use references for sampling methods, qualitative/quantitative research design, and/or supporting information about your topic).

1. Determine your research approach (qualitative or quantitative) and which specific variables you plan to examine. Categorize these variables (nominal, ordinal, etc.).

2. List out your research question(s), and describe them.

3. Determine the sample size you wish to use (needs to be at least 5 people). Generate a list of potential candidates (more than sample size) that you would be able to interview/survey (you don't need to list the people, just use this information to help you determine a sampling strategy). Determine the sampling strategy that you will use to select your participants (your sample size) out of the candidates for your study. What are some potential biases or research problems you could run into?

Ex: Sandra is using a sample size of 5 participants. She has 10 potential candidates who can be interviewed in her study. She then determines a sampling strategy to select 5 participants (sample size) out of the 10 potential candidates.
1. List your references.

Attachment:- Experimental Studies.rar