One potential explanatory variable is the country-level fertility rate (births per woman of childbearing age), which I expect to be negatively related to life expectancy. For instance, I have data from roughly 190 different countries and I am interested in explaining cross-national differences in life expectancy (measured in years). 18.8 Constant Error Variance (Homoscedasticity)ġ4.2 Relationships between Numeric VariablesĬrosstabs, chi-square, and measures of association are valuable and important techniques when using factor variables, but they do not provide a sufficient means of assessing the strength and direction of relationships when the independent and dependent variables are numeric.18.7 The Error Term is Normally Distributed.18.6 The Mean of the Error Term equals zero.18.4 Independent Variables are not Correlated with the Error Term.17.5 Which Variables have the Greatest Impact?.17.2 Incorporating Access to Health Care.16.3.1 Assessing the Substantive Impact.16.2.1 Summarizing Life Expectancy Models.15.9 Adding More Information to Scatterplots.15.4 How Well Does the Model Fit the Data?.15.3.1 Calculation Example: Presidential Vote in 20.14.7 Correlation and Scatterplot Matrices.14.5 Variation in Strength of Relationships.14.2 Relationships between Numeric Variables.13.5 Revisiting the Gender Gap in Abortion Attitudes.13.3 Measures of Association for Crosstabs.12.4.1 Regional Differences in Religiosity?.12.2.1 The Relationship Between Education and Religiosity.12 Hypothesis Testing with Non-Numeric Variables (Crosstabs).11.7 Connecting the T-score and F-Ratio.11.6 Population Size and Internet Access.11.2.1 The Relationship between Wealth and Internet Access.11.2 Internet Access as an Indicator of Development.11 Hypothesis Testing with Multiple Groups.10.3.4 Statistical Significance vs. Effect Size.10.3.2 Returning to the Empirical Example.10.2 Testing Hypotheses about Two Means.8.4.1 Simulating the Sampling Distribution.7.4.2 Intersection of Two Probabilities.7.4.1 Empirical Probabilities in Practice.6.8 Calculating Area Under a Normal Curve.6.7 The Standard Deviation and the Normal Curve.6.6 Dispersion in Categorical Variables?.5.5 Mean, Median, and the Distribution of Variables. ![]() 4.5 Collapsing and Reordering Catagories.2.2 Understanding Where R (or any program) Fits In.1.4.1 Necessary Conditions for Causality.1.4 Observational vs. Experimental Data.An Introduction to Political and Social Data Analysis Using R.
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