Students must work individually on the exam.
A single-page cheat sheet and calculator are allowed; phones and computers are not permitted.
The test comprises 10 points, equating to 10% of the final grade.
For multiple-choice, fill in the bubble for the correct answer.
For numerical questions, write the final answer in the designated box.
Use the outside space for calculations and final sentence responses.
The questions pertain to a graph displaying the total fertility rate (TFR) and female labor force participation rate (LFPR) across 22 OECD countries.
TFR refers to the average number of children a woman has during her lifetime.
LFPR is the fraction of adult women employed or seeking employment.
Graph Type: Identify the type of graph.
Choices: Bar graph, line graph, histogram, pie chart, scatter plot.
Correlation in 1980: Determine the correlation between TFR and female LFPR in 1980.
Choices: -0.6, -0.4, 0, 0.4, 0.8.
β2000 Value: Assess the slope β2000 in the linear regression of TFR predicting LFPR.
Choices: β2000 < 0, β2000 = 0, β2000 > 0, not enough information.
Causality of β2000: Evaluate whether β2000 represents the exact causal effect of women’s labor force on fertility.
Choices: Yes, no, not enough information.
Questions ask about averages of children born to women in Uganda and education completion rates among women in Nigeria.
Average Children in Uganda: About the average number of children women have in Uganda.
Choices: 2.8, 4.5, 5.6, 6.4, 6.6.
Women in Nigeria: Percentage of women (ages 15-49) with no higher education in Nigeria.
Choices: 3%, 10%, 30%, 90%, 97%.
Main Takeaway: Assess the main conclusion related to education and number of children.
Choices related to education and fertility correlation.
India's Absence: Reason for India's exclusion from the figure.
Several potential explanations related to geography, education, or analysis choices.
Questions require interpretation and analysis of figures concerning life expectancy and GDP/capita from the most populated countries.
Questions assess categorical variables, histogram drawing for life expectancy, mean calculation, properties of distributions, and correlation graph interpretation.
Analyzes correlation between mother's education and infant mortality based on data collected across 707 districts in India.
Scatter Plot Assessment: Describe the relationship based on the scatter plot.
Regression Coefficients: Determine values of β1 and β0 in the regression model.
Regression Equation: Write out the regression equation.
Interpret Slope: Explain the significance of the regression slope.
Prediction for 17 Years of Education: Calculate the predicted infant mortality rate for high educational attainment.
Prediction Analysis: Evaluate the sensibility of the prediction.
r2 Interpretation: Calculate and interpret r2 in the regression context, reflecting on how much variance in infant mortality can be explained by education.