Untitled Document - Research Methods

Cumulative Section: - Distinction between “basic” and “applied” research - basic= Focuses on expanding fundamental knowledge and understanding of natural phenomena or principles - applied= Aims to solve practical problems or answer specific questions with...

Cumulative Section: - Distinction between “basic” and “applied” research - basic= Focuses on expanding fundamental knowledge and understanding of natural phenomena or principles - applied= Aims to solve practical problems or answer specific questions with direct real-world applications - Sources of info - Primary= ontain complete descriptions of the collected data and data analyses - secondary= Secondary sources contain only summaries or interpretations - Validities - Construct validity= how well variables are measured and manipulated - Statistical validity= how well the numbers support the claim - Internal validity (12 covered in class)= in a relationship between one variable (A) and another (B), the extent to which A rather than some random other variable is responsible for B - External validity= how well does the study apply to a general population - Reliability vs. Validity in measurement - Research methods - Descriptive= designed to answer questions about the current state of affairs - Correlational= Involves the measurement of two or more relevant variables and an - assessment of the relationship between or among those variables - Pearson Product-Moment Correlation Coefficient= The most common measure of relationships among variable - Experimental=involves the active creation or manipulation of a given situation or - experience for two or more groups of individual - Hypothesis testing - Null hypothesis= Represents a default position or assumption that there is no effect, no relationship, or no difference between groups - Alpha=significance level - p-value=The calculated probability that the observed results occurred by chance, assuming the null hypothesis is true - Type I error = Rejecting the null hypothesis when it is actually true so you ou claim an effect exists when it does not - Type II errors= Failing to reject the null hypothesis when it is actually false so you miss detecting a real effect - Between design= Participants are split into separate groups, where each group experiences only one level of the independent variable - within design= he same participants are exposed to all levels of the independent variable - mixed designs= Combines elements of both between-subjects and within-subjects designs. - - -