This session is dedicated to bridging the gap between the formal course requirements and your personal goals as a researcher. We will begin by completing a detailed Student Needs & Background Questionnaire. Your responses will directly influence how we approach the 14 weeks of instruction, allowing us to emphasize the data collection techniques or analytical methods you find most challenging or intriguing.

This introductory lecture will explore why psychology is fundamentally a science, dispelling the myth that it solely relies on common sense or intuition. We will examine why human intuition is often flawed, using examples like the unexpected positive relationship between text messaging abbreviations and children's verbal reasoning skills to highlight the necessity of empirical research. The core of the session will introduce the scientific method, specifically tracing its evolution from the early empirical method of gathering data without preconceptions to the modern hypothetico-deductive model. Students will learn the critical distinction between theories, which are broad explanations, and hypotheses, which are precise, testable statements derived from those theories. A major theme of the lecture is that scientific research never "proves" a theory to be absolutely true; rather, evidence can only support or challenge it. We will discuss the concept of falsifiability, emphasizing that for a theory to be considered scientific, it must be stated in a way that allows it to be proven false. The lecture will also underscore the importance of replication and attempting to disconfirm theories, as testing the limits of an effect is crucial for advancing psychological knowledge. Furthermore, we will break down the practical steps of planning an investigation, focusing on four key interdependent decision areas: identifying variables, selecting appropriate samples, determining the research design, and planning the data analysis. Students will be introduced to the concept of operationalizing variables, ensuring that abstract concepts like aggression are translated into clear, measurable terms. Finally, the lecture will briefly contrast traditional quantitative methods involving numerical data with qualitative approaches that focus on meaningful verbal information, acknowledging the diverse ways psychologists study human behavior.

This lecture provides a foundational overview of how social scientists, particularly psychologists, measure phenomena and select participants for their research. We will begin by exploring the concept of variables, defining them as observable or hypothetical phenomena whose changes can be tracked and quantified. Because many psychological concepts, like anxiety or intelligence, are not directly observable, we will discuss how researchers treat them as hypothetical constructs. To study these constructs objectively, you will learn how to create precise operational definitions that detail the exact steps taken to measure a phenomenon. The critical principles of measurement reliability—meaning consistency—and validity—ensuring an instrument measures what it claims to—will also be introduced as pillars of credible research. The second half of the lecture shifts to the crucial topic of sampling, examining how researchers select representative individuals from a larger target population. We will compare equal probability selection methods, such as simple random and stratified sampling, against non-random techniques like quota, opportunity, and snowball sampling. Furthermore, the lecture will address the complexities of sample size, explaining why a larger sample is not always better and how it relates to statistical power. We will also explore the modern advantages and logistical challenges of sourcing research participants through online platforms. Finally, we will unpack the fundamental theoretical division between quantitative methodologies rooted in positivism and the qualitative approach that emphasizes the rich, subjective meanings of human experience.