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Consider a family saving function for the population of all families in the United States: sav = βo β₁inc βzhhsize β₃educ β₄age u, where hhsize is household size, educ is years of education of the household head, and age is age of the household. Suppose that the sample includes only families whose head is over 25 years. Do we get unbiased estimators of the β? Explain.

User BerndK
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Final answer:

A scatter plot can be created by plotting the year and number of family members attending college. The least-squares line can be calculated to represent the best-fit line through the scatter plot points. The y-intercept of the line does not have a practical interpretation in this context.

Step-by-step explanation:

a. Scatter plot:

A scatter plot of the data can be created by plotting the year on the x-axis and the number of family members attending college on the y-axis. Each data point represents a specific year and the corresponding number of family members attending college.

b. Least-squares line:

The least-squares line represents the best-fit line through the scatter plot points. It can be calculated using a method called linear regression. The equation of the least-squares line is in the form y = a + bx, where y is the dependent variable (number of family members attending college), x is the independent variable (year), and a and b are the coefficients.

c. Meaning of the y-intercept:

The y-intercept, a, represents the estimated number of family members attending college when the year is 0. However, since the year variable is not meaningful for this specific scenario, the y-intercept does not have a practical interpretation in this context.

d. Correlation coefficient:

The correlation coefficient measures the strength and direction of the linear relationship between the year and the number of family members attending college. It ranges from -1 to 1, where -1 indicates a strong negative correlation, 1 indicates a strong positive correlation, and 0 indicates no correlation. The correlation coefficient can be used to determine if the relationship between the variables is statistically significant.

User Noha
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