Chapter 17: Advanced Regression Topics

A comprehensive set of vocabulary flashcards designed to assist in understanding advanced regression topics related to life expectancy analysis.

Life Expectancy

The average period that a person may expect to live, related to factors such as health care access.

Multiple Regression Models

Statistical techniques that evaluate relationships between multiple independent variables and a single dependent variable.

Urban Areas

Locations characterized by higher population density and vast human-built features compared to areas surrounding it.

Doctors per 10,000

A direct measure of health care access, indicating the number of doctors available for every 10,000 individuals in the population.

R-Squared (R²)

A statistical measure that represents the proportion of variance for a dependent variable that's explained by independent variables in a regression model.

Adjusted R-Squared

A modified version of R² that accounts for the number of predictors in the model and adjusts the value accordingly.

Root Mean Square Error (RMSE)

A measure of the differences between values predicted by a model and the values observed.

Fertility Rate

The number of live births per 1,000 women of childbearing age in a given year.

Mean Years of Education

The average number of years of education received by people aged 25 and older in a given population.

Logarithmic Transformation

A technique to adjust the scale of data, often used to reduce skewness or recognize curvilinear relationships.

Bivariate Relationship

A relationship involving two variables that can be assessed through correlation or regression analysis.

Collinearity

The occurrence of high correlation between two or more independent variables in a regression model.

Variance Inflation Factor (VIF)

A measure of how much the variance of an estimated regression coefficient increases when your predictors are correlated.

Standardized Coefficients

Coefficients derived from standardized data allowing comparisons between variables measured on different scales.

Statistical Significance

The determination that an observed effect in data is unlikely to be due to chance alone.

Two-tailed Test

A statistical test that determines if there are any significant differences regardless of direction.

One-tailed Test

A statistical test that determines whether the correlation is significant in a specific direction.

Model Interpretation

The process of explaining the meaning and implications of the results from a statistical model.

Missing Data

The absence of values for certain observations or variables in a dataset.

Correlation Matrix

A table showing correlation coefficients between variables, allowing assessment of relationships.

Scatterplot

A graphical representation of the relationship between two quantitative variables.

Residuals

The differences between observed and predicted values in regression analyses.

Curvilinear Relationship

A relationship between two variables that does not follow a straight line but instead forms a curve.

Diminishing Returns

A concept in economics stating that after a certain point, the addition of an input yields progressively smaller increases in output.

Z-Scores

Standardized scores indicating how many standard deviations an element is from the mean.

Outliers

Observations that lie outside the overall pattern of distribution in the data and can significantly affect statistical results.

Stargazer Package

An R package used for creating well-formatted regression tables and summary statistics.

DescTools Package

An R package providing tools for descriptive statistics and visualization in data analysis.

Statistically Significant Impact

An outcome where the probability that the results occurred due to chance is very low.

Influence of Variables

How changes in independent variables affect the outcome of the dependent variable.

Data Imputation

Methods for estimating missing data points within a dataset.

Cross-national Data

Data collected from multiple countries, often used for comparative studies.

Model Fit

How well a statistical model describes the data it is intended to represent.

Policy Implications

Consequences or required actions resulting from the results of research or study findings.

Factor Analysis

A statistical method used to describe variability among observed, correlated variables in terms of fewer unobserved variables.

Economic Development

The progress of an economy in terms of wealth and living standards.

Regression Coefficient

A value that represents the relationship between an independent variable and the dependent variable in a regression analysis.

Sample Size

The number of observations or data points collected for analysis.

Null Hypothesis

A general statement or default position that there is no relationship between two measured phenomena.

Alternative Hypothesis

What researchers aim to support, proposing that there is a statistically significant effect or difference.

Significance Level (p-value)

The probability of rejecting the null hypothesis when it is true; lower values indicate stronger evidence against the null hypothesis.

Diminished Impact

A reduced effect or influence of one variable on another.

Data Collection Challenges

Issues encountered when gathering data, including accuracy, completeness, and availability.

Life Expectancy Model

A statistical model that predicts average lifespan based on various independent health-related factors.

Health Care Policy

Strategies and decisions regarding the distribution and access to health resources and services.

Cross-sectional Data

Data collected at a single point in time, often used for comparative analysis.

Longitudinal Data

Data collected from the same subjects repeatedly over a period of time.

Statistical Modelling

The process of creating abstract models to represent real-world processes using statistical techniques.

Research Methodology

The strategy or technique adopted in a study to analyze and present data.

Theoretical Framework

A structure that can hold or support a theory of a research study.