Look at the Results in Table 1 Below -Imagine You Are Watching a Political Talk Show (Perhaps One

question 1

Multiple Choice

Look at the results in Table 1 below.
Table 1: Culture and Democratic Survival
Dependent variable: Probability of Democratic Survival


$\begin{array}{lc}\hline \text { Independent variables } & \text { Model 1 } \\\hline & \\\text { Muslim majority } & -0.46(0.28) \\\text { Catholic majority } & -0.41^{*}(0.20) \\\text { GDP per capita } & 0.0001^{* *}(0.00003) \\\text { Growth in GDP per capita } & 0.02^{* * *}(0.01) \\\text { Oil producer } & 0.43(0.31) \\\text { Effective number of ethnic groups } & -0.09 * * *(0.05) \\\text { Constant } & 1.88^{*}(0.28) \\\text { Observations } & 1784 \\\text { Log-likelihood } & -161.41 \\\hline \text { Robust standard errors in parentheses. "greater than } 90 \% \text { significant; } \\{ }^{* *} \text { greater than } 95 \% \text { significant; }{ }^{* *} \text { greater than } 99 \% \text { significant. } \\\hline\end{array}$
-Imagine you are watching a political talk show (perhaps one of the ones that are shown on Sunday morning, or perhaps The Daily Show) and the pundits are discussing problems with the democratization process in Iraq. One of the guests claims that a key factor making it unlikely that democracy could survive in Iraq (even if it were established there) . is that there are too many different ethnic groups in the country. Does the empirical evidence in Table 1 support such a claim?

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Definitions:

Standard Deviation

A measure of the dispersion or variation in a distribution, indicating how much the individual data points deviate from the mean.

Sample Size

Sample size refers to the number of observations or data points collected in a statistical study, which is critical for ensuring the reliability, validity, and generalizability of the study's results.

Probability of Error

Probability of error refers to the likelihood that a statistical decision or hypothesis test will result in a wrong conclusion.

Test Power

The probability that a statistical test will correctly reject a false null hypothesis, essentially the ability of a test to detect an effect if there is one.