Category Archives: Uncategorized

1. Summarizing raw data: -Numerical: %, averages, frequency tables…-Graphical: visual representation of data Relative frequency: frequency of x / total number of responses (e.g., n% of respondents did x). 2. Central Limit Theorem: If taking an infinite number of samples from a given population, the means of these samples would be normally distributed. Normal curve:Continue reading “Class #12: Descriptive Statistics”

1. I added other important ethical issues to the last post (Class #10), including “Vulnerable populations” and “Scientific misconduct”. 2. Types of replication studies: –Direct replication: Straight from the source; could fail due to the change of the historical background–Conceptual replication: Re-testing the same theoretical idea using different manipulations-Replication-plus-extension: Re-testing the original study + addingContinue reading “Class #11: Replication and Good Science”

1. Researcher’s Obligations: To provide information; to protect the rights and welfare of the participants 2. The Tuskegee Syphilis Study: Participants were not treated respectfully Participants were harmed Participants were targeted, disadvantaged social group 3. The Milgram Obedience Studies: Lesson: Researchers must balance the risk to participants with benefit to society. 4. The Belmont ReportContinue reading “Class #10: Ethics”

1. Economic sample – provides a reasonably accurate estimate of the population at reasonable effort and cost. 2. Things that influence the accuracy of a sample:-Sample size (the larger, the better)-Population size (the larger population, the larger sample needed)-Variance of the data (larger sample size will capture the extreme scores better) 3. Random Samples (Examples):Continue reading “Class #9: More about sampling”

1. Back to concerns about questionnaires: Potential Response Bias – People might tend to answer in a certain way that’ll produce unintended effects. e.g. Social Desirability: In the Burrito Kingdom, every citizen might feel pressured to report that they like burritos. Solutions: Word questions as neutrally as possible; Assure the Ss’ anonymity; Forced-choice approach, items ofContinue reading “Class #8: Questionnaire and Sampling”

First of all, CONGRATULATIONS for surviving the first exam! Please do not hesitate to contact Eranda or me if you have any questions about it. Back to the take-away points: 1. How to test validity? Face validity: the extent to which a measure appears to measure what it’s supposed to measure Construct Validity: Testing theContinue reading “Class #7: Vadility and Test-bias”

1. Measures of Variance: Observational Physiological Self-ReportConverging operations: Using multiple methods to measure variance 2. Measurement Scales-Nominal variables-Continuous variables: Ordinal, Interval, Ratio 3. Observed Score = True score 🙂 + Measurement Error 😦 We want to minimize measurement error, but things happens: Transient Participant State (e.g. mood) Stable Attributes  (e.g. personality) Situational Factors (e.g. noisy environment)Continue reading “Class #6: Measuring Behavior”

1. Statistics are everywhere. 2. Numbers don’t mean anything on their own. One definition of statistics is “the process of adding meaning to data”. 3. The shape of data is called their distribution. The classic “bell curve” represents a normal distribution. 4. Statistics places great importance on the presentation of data; visualising statistics helps us toContinue reading “Class #5: The Joy of Statistics”

1. The types of studies you choose could affect: The way you collect data The statistics you use The conclusions you can make 2. Psychological science is about looking for and examining systemic behavioral variability. Behavior varies among individuals, changes over time and situations. 3. The Five Factor Model (OCEAN*) explains variability between people, withinContinue reading “Class #4: Variability”

1. Science self-corrects by comparing the predictions of a theory with empirical, systematic observations and then adjusts the theory in order to fit the observations. 2. A good theory is parsimonious (simple), testable (falsifiable), and interesting. 3. Types of studies (with examples): Descriptive: 77.8% students of our class are female, and… Correlational: High attendance ratesContinue reading “Class #3: Scientific Process, Types of Studies”