Monthly Archives: October 2019

1. What makes studies experimental?– Researcher manipulates one variable (the Independent Variable) – Researcher controls the group assignment (experimental groups + control group [baseline])– Researcher controls extraneous variables that influnce participants’ behavior (confounds) 2. In experimental studies, we are interested in how one (or more) variable [Independent Variable] changes behavior [Dependent Variable]. NOT just howContinue reading “Class #16: Experimental Research”

1. Regression analysis: drawing a straight line through the scatter plot, mathematically. Regression analysis can be used to predict the relationship between 2 or more variables. 2. Simple Linear Regression: y = B0 + B1 x  e.g.: Predicting your grade of PSY310 from the frequency of checking this blog. >:) 3. Multiple Regression Analysis: predicting the outcomeContinue reading “Class #15: Regression”

1. Interpreting correlations: Because 1) We don’t know the direction; 2) There could be a third variable involved. 2. Statistical Significance* (p<= .05) for correlation coefficient means: the correlation calculated on the sample has a very low probability of being .00 in the population.In other words, when p<.05, it’s unlikely that the correlation was notContinue reading “Class #14: More on Correlation”

1. Correlations answer questions of the relationship between two variables. Scatter plots is one way of determining the form of relationship. 2. Correlation coefficient (r) quantify the linear relationship between two variables.Pearson r: A statistical index of how 2 variables systematically relate to one another in a linear fashion. Range: -1 to +1 Sign (direction):Continue reading “Class #13: Correlation”

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”