MAX 201 Exam #2 Study Guide

What is a research question?

A clear and specific question about the social world that can be answered through the collection and analysis of empirical data.

Criteria for a good research question

Empirical, Generalizable, Clear, focused, and specific, Testable/answerable with data, Possess Theoretical significance, Practical relevance, and Originality.

Null Hypothesis (H0)

Assumes there is no relationship between the variables, and differences found in the sample are not found in the population.

Research Hypothesis (HR)

States your expectation about the relationship and is potentially supported if you reject the null hypothesis.

Independent Variable (IV)

The predictor variable.

Dependent Variable (DV)

The outcome variable.

Deductive research

A process that starts with a theorized relationship and aims to collect and analyze data to see if the research hypothesis is supported.

Sampling vs. Census

Sample: A selection of cases to estimate characteristics of the population; Census: Data collected from the entire population.

Sampling Error

Error that occurs when a sample does not accurately represent the population.

Statistic vs. Population Parameter

Statistic: A value obtained from a sample; Population Parameter: The true mean of the population being estimated.

Normal Distribution Characteristics

Sampling distribution of means is always normal, most sample means fall close to the true population mean, and they are scattered as per any normal curve.

Confidence Intervals

Indicate how confident you are that sample values are close to the true population mean, with non-overlapping intervals indicating differences.

Inferential Statistics

Using characteristics of the normal distribution to make inferences from the sample to the population.

Logic of Hypothesis Testing

Assume nothing is going on (H0 is correct); determine if there is less than a 5% chance that H0 is correct.

Chi-Square Test P-value Interpretation

If p-value < 0.05, reject H0 and conclude the relationship is significant.

Degrees of Freedom in Chi-square

df = (number of rows - 1) × (number of columns - 1).

Causation Requirements

Empirical correlation between variables, time order, and non-spuriousness.

Spurious vs. Non-Spurious Relationships

Spurious: Relationship becomes non-significant with a control variable; Non-Spurious: Relationship remains significant.

Specified Relationship

When the relationship is significant for some categories of a control variable but not for others.

Confounding Variables

Variables that influence both IV and DV creating the appearance of a relationship.

Mediating Variables

An additional independent variable that explains the relationship between IV and DV.

t-Test

Assesses the null hypothesis that there is no difference between two subgroups in the population.

Pearson’s r Correlation Coefficient

Measures the extent to which two variables move together in a predictable way.

Regression Equation for Best Fit Line

Y = a + b(X), where Y is the dependent variable, a is the Y intercept, b is the regression coefficient, and X is the independent variable.

Best Fit Line

The line with the smallest differences between values predicted and observed.

Regression Coefficient (b)

Indicates how much the dependent variable changes with each unit increase in the independent variable.