RESEARCH OVERVIEW Research Basics Steps in the Research

RESEARCH OVERVIEW Research Basics

Steps in the Research Process 1. 2. 3. Develop research Idea Search literature & develop hypothesis Select a research design & method � � � 4. 5. 6. 7. Nonexperimental or experimental Manipulations and measurement Sampling and recruitment plan Conduct study Evaluate data Report results Refine/Retest

Designing a Study Which strategy, design, and/or method should be used to test the hypothesis? � Decision based on many factors Advantages & limitations of the strategy/design/method State of current knowledge on topic Practical issues – money, time, resources Ethical issues

Strategy, Design, & Method Research Strategy � General approach to research determined by the kind of question posed by the researcher Nonexperimental, Experimental? Quasi-experimental or Research Design � Plan for implementing research strategy Groups versus individuals Same individuals versus different individuals Number of variables manipulated and measured Research Method � How are the data being collected?

Research Strategies General approach and goals of a study Nonexperimental � Descriptive or Single-variable � Predictive Quasi-Experimental Can be some gray area � Sometimes a strategy is linked to a method � Sometimes a study is somewhere in between two strategies � A single study may have multiple hypotheses, use more than one research strategy, and also use different methods.

Descriptive or Single Variable Research Merely describes a variable or variables Not able to say anything about whether variables are related nor make cause-effect statements

Predictive Correlational � Investigates relations between 2 or more variables � Not explaining the relationship (no causal assignment) � Identifying patterns in data Direction Strength Form Could have collected the data through a survey, observation, from existing records (i. e. , archival), etc.

Correlational 8 1. Direction of relationship Positive, Positive SAME DIRECTION Negative, or No relationship No relation Negative OPPOSITE DIRECTION

Correlational 2. Strength of relationship � Correlation Ranges coefficient Strongest Relationship from -1. 00 to +1. 00 -1. 00 reflects a perfect negative relationship +1. 00 reflects a perfect positive relationship Closer to zero reflects a weaker relationship

Correlational 3. Form of relationship � Linear relation Change is fairly constant � Curvilinear Change relation is not constantly the same

Guess the Direction & Size of Relation Positive Strong Negative Weak Negative Perfect No Relation

Correlational Predictor Variable X-axis Longitudinal � Current measure Thought to be the cause Criterion Variable Y-axis Longitudinal � Future measure Thought to be the effect Sometimes also called the DV or the outcome variable

Correlation does not imply causation Alternative Explanations � Directionality problem Time spent playing violent videogame � Third-variable Lurking Aggressive behavior problem variables, third variables, confounds Violent videogames Parental Monitoring Aggression

Quasi-experimental Attempts to answer cause-effect questions However, includes a flaw that prevents this Usually examining pre-existing variables (i. e. , characteristics about participants that can’t be manipulated) or participants self-select themselves into groups � I. e. , “Subject”, “Participant” “Quasi-independent” � E. g. , gender, smoking status

Explanatory Experimental Research Determine one variables cause changes in another variable � Involves manipulation of variables, random assignment, & control Independent Variable (IV) – manipulated � Randomly assigned to levels/conditions of the IV Random assignment is a procedure used to eliminate participant variables as alternative explanations Dependent Variable (DV) – measured Hold all other variables constant Variable X (Cause) Variable Y (Effect)

Other interpretations? ? ? 16 Incidental (extraneous) variables � Other variables that are not the focus � Confound variables Vary reliably with the manipulated variable Serve as an alternative explanation Sometimes referred to as “third-variables” or “lurking variables”

More on Independent Variables Does 1 IV have an effect on the DV? � The terms – levels, conditions – have similar meaning. Interaction effects (e. g. , Factorial Designs) � Do IVs interact to influence a DV? � The terms – levels, conditions – now have different meanings. Levels refer to the different amounts of each IV. Conditions refer to the different combinations of the levels of the IVs.

Example Task Difficulty (A) Easy (A 1) Presence of others (B) Difficult (A 2) Alone (B 1) Easy task alone Difficult task alone Audience (B 2) East task w/ audience Difficult task w/ audience • This study has two independent variables (IV) • (IV) Presence of others • 2 levels: Alone vs. Audience • (IV) Task difficulty • 2 levels: Easy vs. Difficult • 4 conditions

Think this through… Explain why we cannot make causal claims with correlational data. � Be specific. Explain why we can make causal claims with experimental data (assuming well-designed study). � Be specific.

Mini-Review 1. 2. 3. 4. Explain why we cannot make causal claims with correlational data. Explain why we can make causal claims with experimental data (assuming well-designed study). What’s the difference between levels and conditions? If I said that the correlation between anxiety and depression was. 75, how would you interpret this correlation coefficient?