Slides 18, 19 (˶ᵔ ᵕ ᵔ˶) Flashcards
What is the difference between correlation and causation?
Correlation indicates a relationship between two variables, while causation implies that one variable directly affects the other.
Understanding the distinction is crucial in statistics and research methodologies.
What are the two conditions for omitted variable bias?
- Z is determined by X
- Z is correlated with Y
These conditions must hold for omitted variable bias to affect the relationship between X and Y.
What is an omitted variable?
A variable that is not included in the analysis but affects the dependent variable.
It can lead to biased estimates if not accounted for.
What are the types of models mentioned?
- Multiple regression models
- Nonlinear models
- Interaction terms
- Nonparametric models
Each model type serves different purposes in statistical analysis.
Fill in the blank: The term _______ refers to the bias introduced by excluding relevant variables from a model.
omitted variable bias
What is the purpose of ANOVA in statistics?
To compare means across multiple groups.
ANOVA stands for Analysis of Variance.
True or False: Multicollinearity refers to the situation where independent variables in a regression model are highly correlated.
True
This can lead to unreliable coefficient estimates.
What does residual analysis help to identify?
Potential problems with a regression model.
It assesses how well the model predictions match the actual data.
List three types of sampling techniques.
- Random sampling
- Stratified sampling
- Systematic sampling
Each technique has its strengths and weaknesses in research design.
What is the role of interaction terms in a regression model?
To assess the combined effect of two independent variables on the dependent variable.
This allows for more complex relationships to be modeled.
Fill in the blank: A model that includes both linear and nonlinear relationships is referred to as a _______ model.
nonlinear
What does the term ‘residual’ refer to in regression analysis?
The difference between observed and predicted values.
Residuals are key for assessing model fit.
What is the purpose of using visual analytics in data analysis?
To help interpret and communicate data findings effectively.
Visualizations can reveal patterns that might not be apparent in raw data.
True or False: The presence of outliers does not affect the results of a regression analysis.
False
Outliers can significantly skew the results and interpretations.
What is a common method for assessing the fit of a regression model?
R-squared value.
It indicates the proportion of variance explained by the model.
What does the term ‘scientific paper’ imply in the context of statistical analysis?
A document that presents research findings and methodologies.
It often undergoes peer review before publication.
