What topic would you like to know more about? How would you propose studying this topic?
#20: Lab 3: Self-Administered Mail Survey, Due Date: 23-JUL-2017
Select one of the topics listed below and construct a self-administered mail survey to study that topic. You should consult the chapters in your text to make sure you include all of the essential components of this type of survey.
Your paper will include both a cover letter and the final instrument (survey). A sample lab is included below (titled “Sample Lab 3”). Please review it before beginning this activity.
Topics (choose one):
Satisfaction with health insurance
Happiness in current job/career/occupation
Voting behavior in last general election
Diet and exercise
School budgeting process
Leisure time
Spending habits
Your paper should also address the following points:
Who is your sample? How will you identify them? What type of sample will you use & why? How will you increase your response rate?
Your survey must include a total of at least 10 questions. The following types of questions must be included at least once:
contingency question that includes at least one contingency
matrix question that includes at least 5 questions
open-ended question
#21: Final Project Topic, Due Date: 23-JUL-2017
What topic would you like to know more about? How would you propose studying this topic?
Decide on a topic for your research proposal
Select a topic for your Final Project and state the specific hypothesis(es) that you wish to examine. Do not select hypotheses used in class, the readings, or discussion boards.
Operationalize your concepts and identify the independent variable and dependent variable in the hypothesis.
#22: Submit Research Proposal Update, Due Date: 06-AUG-2017
Submit a Final Project Update and Questions to your professor. Raise any questions you may have about constructing a research proposal to the professor. Are you having trouble getting started? Are you making progress? Please review the Final Project: Research Proposal in the syllabus for assignment details.
#23: Lab 4: Quantitative Data Analysis, Due Date: 06-AUG-2017
Your finished product should be approximately two-and-a-half pages in length, double-spaced in 12-point font with 1-inch margins.
This lab introduces you to quantitative data analysis. For this lab, you will access a resource at the University of Michigan, where data sets are stored. Under most circumstances, if the federal government has paid for research, the researchers must make the data available to the public after just a few years. Most data sets are sent to this resource.
This lab requires that you very carefully follow all of the instructions. You must complete each step in the order presented.
Go to the website: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03580
This should return “# 3580: National Household Survey on Drug Abuse, 2001”. Click on the link.
Scroll down to “Analyze Online”
Select “Analyze Data using SDA”
Click on “Create new account” to set up an account.
We are ready to begin our quantitative data analysis. We will do two steps: univariate and bivariate analysis. When a data set is entered into a computer program, variables or questions must be given short names – 8 or fewer characters. So, for each of the variables that we are going to examine, there will be a short name and a longer “question” that explains it.
Univariate analysis allows us to look at one variable at a time, as the name implies. With discrete or non-continuous variables (nominal and ordinal), the most common statistics that we use are the frequency and the percent. Neither of these statistics works well with continuous variables, as there are too many attributes (possible responses). Instead, with continuous variables (interval and ratio), we use measures of central tendency such as the mean, median, and mode. For this lab and this course, we will examine only nominal variables.
Bivariate analysis allows us to examine the relationship between two variables. In addition to the frequency and percent of the variables, we can see if there is an association between the variables (examine %). It is difficult to establish causality using bivariate analysis, since relationships among social variables are complex and rarely reduced to simply two variables. This is an important step to determine if and how variables are related to one another.
Univariate Analysis
The first step in doing data analysis is to find out how subjects (people in this case) responded to our questions. We are using a survey conducted by the National Institutes of Health (NIH), but the same procedures are involved with any quantitative data set that you will use.
As you can tell by the title of the study, the researchers asked a very large sample (over 55,000) of Americans about their drug-use behaviors. There are many variables in this study, but we will focus only on a few, so that you can get an idea of what goes into data analysis.
Look to the right side of the screen and find “SDA Frequency/Crosstabulation Program”
ROW: list the following variable short names (all caps or all lower case) with only a space between each variable: cigever alcever mjever cocever crkever herever irsex. Notice there are no upper/lower case and no commas. This is important.
PERCENTAGING: click only total (remove other checks)
Click “run the table”
You have just created a lot of information, most of which we are going to ignore! If you closely examine the line that begins with “Row,” you will find the variable short name and a longer explanation.
Just below that is a table “Frequency Distribution.” You can see what percentage of the subjects answered “yes” or “no” to each of the questions you listed in the prior step.
Examine your data and complete the following:
