Chapter specific application exercises will help you think about research design in practice or have you explore a relevant resource.

Exercise 1: Basic Statistics

For the variables SMCS and KWA in Exhibit 6.1, compute mean, median, mode, range, variance, and standard deviation.

Exercise 2: Brand, Color, and Gender Preferences

Let’s hypothesize that men and women differ in their preferences for clothing brands and for color. In a setting such as a classroom, cafeteria, or library, look at the T-shirts and sweatshirts people are wearing. For each person, record your observations of gender, and the color and “brand” (Gap, Nike, a university name, etc.), if any, on each shirt. Produce two contingency tables—gender by color preference and gender by brand.
What conclusions can you come to about how color and brand preferences differ by gender?
Note that this assignment is not quite as simple as it appears because as soon as you start recording color, you will need to make a typical research decision—setting up your own categories. The number of color categories is potentially almost unlimited, so you will want to make that number manageable. How many categories will you set up, and how will you decide what category indeterminate colors (“could be this; could be that”) will be assigned to? How will you handle clothing that promotes a cause or a political candidate rather than a brand? For some help with this assignment, you can jump forward to Chapter 12.

Exercise 3: “The Internet of Things”

Find the May 14, 2014, Pew Research Center Internet, Science & Tech Project report on “The Internet of Things” at www.pewinternet.org/2014/05/14/internet-of-things. The Internet of Things, or IoT, is considered the next technol­ogy megatrend in which anything from fitness bracelets to jet engines will be connected to the Internet to transmit and share data. In the report and summary, you will find six themes related to the topic of embedded and wearable computing to which experts were invited to respond. For example: “The Internet of Things and wearable computing will progress significantly between now and 2025.” Select one of the themes you will find in the above report and write it as a Likert-type question (revisit Chapter 5 for help). Get responses to your question from two different cat­egories of people (for example, two different academic majors, or two different class years). Get at least five people in each category. Assign each point in your scale a number so that you can record a score on the question for each respondent. Compute measures of central tendency and of dispersion for each category of respondent and report how these statistics are similar or differ.

Exercise 4: A Social Media Study

Visit LinkedIn.com—the social media site for professionals. Information for some members that is publicly available includes academic qualifications, employment history, group or organizational affiliations, and number of individual connections. Select at least two individuals and look at such information.
Formulate your own research questions about LinkedIn members. For example, are women likely to have more connections than men? Are members with PhDs likely to have more group or organizational affiliations than mem­bers with bachelor’s degrees?
Note that some of the information displayed can be treated as continuous (the number of academic degrees or jobs) and some as categorical (the type of degree or job). Which type of data should you prefer to best answer each of your research question(s)? Produce a table of descriptive statistics that will answer your research question(s). What confi­dence do you have that your results accurately reflect all LinkedIn members of the type you sampled? Revisit Exhibit 6.1 for examples of categorical and continuous data.
Note that this mini-assignment includes almost all the elements of a full communication research study—developing a focus for your study, writing a specific research question, planning your statistical analyses, deciding what type of data to collect and how to collect it, and presenting your results. Note also that deciding what type of statistical analyses and reporting you will do precedes your data collection. If you are interested in continuous data, you will not design a study that collects only categorical data. You need a defensible and demonstrable connection between your initial theory and research question(s), the data you are interested in, and your research method(s).

Note: You can access the information you will need for this project in two ways:

• Search for someone you know or think may be a member of LinkedIn using the “Find a Colleague” window on the home page: www.linkedin.com. This option avoids having to register, but limits you to publicly available information.
• Register with LinkedIn using the “Get Started” window on the home page. This option will give you access to more—members-only—information, as well as enabling you to post your own information.