class: center, middle, inverse, title-slide # Day 1 ## Quantitative research ### Michael W. Kearney📊<br />School of Journalism <br />Informatics Institute <br />University of Missouri ### <table style="border-style:none;padding-top:30px;" class=".table"> <tr> <th style="padding-right:75px!important"> <a href="https://twitter.com/kearneymw"> <i class="fab fa-twitter"></i> </a> </th> <th style="padding-left:75px!important"> <a href="https://github.com/mkearney"> <i class="fab fa-github"></i> </a> </th> </tr> <tr style="background-color:#fff"> <th style="padding-right:75px!important"> <a href="https://twitter.com/kearneymw"> <span class="citation">@kearneymw</span> </a> </th> <th style="padding-left:75px!important"> <a href="https://github.com/mkearney"> <span class="citation">@mkearney</span> </a> </th> </tr> </table> --- class: inverse, center, middle ## Agenda --- ## Agenda + Review scientific method + Review research design --- ## Scientific Method - Try to be "objective" - Theories should be falsifiable - Research should be reproducible - Knowledge is cumulative and provisional --- ## Research questions - Important to journalism/mass communication - Contribute to scientific understanding/literature - Personally interesting - Unresolved or unknown --- ## Research designs - Survey - Experiment - Content analysis --- ## Measuring constructs - Conceptual (i.e., definition) - Operational (i.e., indicators) --- ## Hypotheses to design - Hypothesis: Expectations of co-variations between two or more variables - Design must test hypotheses - Unit of analysis - Observation of variables of interest - Observation of mechanisms/explanatory - Observation of other relevant or confounding variables --- ## Course Objectives - Describe journalism/media relevant research questions and hypotheses - Evaluate and deduce observable implications from mass media and journalism theories - Explain statistical procedures and their appropriate usages - Apply statistical procedures to relevant research problems - Synthesize results from statistical analyses into well-written and well-structured essays - Demonstrate how to use R for statistical analysis --- ## Why R? - SPSS/SAS/stata all cost money - R is open source, free, and at cutting edge - Learning R means learning programming (web scraping, automated work flows, etc.) --- ## Exams - Two take-home exams - Each exam should take anywhere from 2-5 hours - More details as exams get clsoser --- ## Homework assignments - Assignments/submissions on Canvas - All assignments will require use of R --- ## Weekly Activities - Various in-class activities --- ## Course Outline - Research design - Group comparisons - Correlations and factors - Linear models - Advanced models - Text analysis - Data science --- ## Instructor - Office: - Lee Hills Hall 314 - Thursdays 11-2pm - Email: kearneymw@missouri.edu --- ## Introductions - Your full name - Where you are in the program? - What are your research interests? - What stats courses have you taken? - What do you hope to learn? --- class: inverse, center, middle # Quantitative research basics --- ## Defining variables **Conceptual definition** - A description of a variable's **theoretical** meaning. **Operational definition** - A description of a variable's **observable** meaning. --- ## Example - Let's walk through an example of defining variable(s) and thinking about it in more practical terms --- ## Class size Define the construct *class size* - **Class size** refers to the... - Physical dimensions of the classroom - The number of students - The mass of the students --- ## Comparing classes sizes Let's say we want to compare two observed class sizes - **CLASS 1**: 30' x 30' room with 5 students weighing 1500 total lbs - **CLASS 2**: 20' x 20' room with 10 students weighing 1250 total lbs --- ## Defining "class size" - **CLASS 1**: 30' x 30' room with 5 students weighing 1500 total lbs - **CLASS 2**: 20' x 20' room with 10 students weighing 1250 total lbs - If we define class size **physical space**, class 1 is biggest - If we define class size as **number of students**, class 2 is biggest - If we define class size as **mass of students**, class 1 is biggest Is any definition right or wrong? --- class: inverse, center, middle # Your turn --- ## Media exposure - Conceptual definition: - Operational definition: --- ## Views on climate change - Conceptual definition: - Operational definition: --- ## Coverage of environmental issues - Conceptual definition: - Operational definition: --- ## Accuracy in reporting - Conceptual definition: - Operational definition: --- ## Fake news - Conceptual definition: - Operational definition: --- ## Social media use - Conceptual definition: - Operational definition: --- ## Political ideology - Conceptual definition: - Operational definition: --- ## Perceived role of journalists - Conceptual definition: - Operational definition: --- # IVs and DVs class: inverse, center, middle --- ## Classifying variables - Variables can be classified according to their status in a theoretical and/or statistical model - There are several different labels applied toward this end, but for the most part they all do the same thing - Variables that represent the *cause* - Variables that represent the *effect* --- ## Terminology - The cause is the **independent** variable - The effect is the **dependent** variable - There's also exogeneous and endogenous, predictors and outcomes, and probably some other synonyms --- ## Cause `!=` cause - Although we use the cause/effect heuristic when modeling the relationship between two variables, we usually acknowledge multiple, reinforcing, or some underlying "root" causes - As long as we all know that, the cause/effect heuristic is still helpful for organizing our theoretical and statistical models - Bad reporting of scientific research happens when we take cause/effect terminology too literally --- class: inverse, center, middle # Your turn --- ## IV or DV? - Sun - Surface temperature --- ## IV or DV? - Reading - Knowledge --- ## IV or DV? - Public perceptions of an event - Reporting information about an event --- ## Independent or dependent? - Breakfast - Health --- ## Independent or dependent? - Exercise - Health --- ## Independent or dependent? - Social media - Face-to-face interaction --- # Hypotheses/research questions --- ## Relationships between variables - Research questions ask about the relationship between two or more variables - These questions can guess direction (e.g., positive vs negative) but I think that kind of defeats the purpose - Hypotheses predict the relationship between two or more variables - Hypotheses can either predict **whether** there is a relationship or what **direction** the relationship is in > Hypotheses allow for more definitive inferences --- ## RQs/Hs - Use **research questions** when there isn't a lot of research in an area and the theory isn't clear about what exactly to expect - Otherwise, use **hypotheses**