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Answer :
Answer:
Extrapolation
Step-by-step explanation:
From the linear regression plot created in the picture given, se could see that Tha percentage of student covered by the the plot is just above 16%. Therefore, to predict the percentage of the number of juvenile violent crime arrests would be in a state if 25% of children are not in school or in the labor force will require us to assume that the current trend continues into the future. Hence, we use the information and indications we have at present to make prediction into the future based on the assumption that we the current trend will remain relevant and applicable. This assumption into the future based on current trend is called EXTRAPOLATION.
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Final answer:
The question involves predicting juvenile violent crime arrests based on the percent of children not in school or the labor force using a least-squares regression line. By finding the point on the regression line that corresponds to 25% on the x-axis, you can determine the predicted number of arrests.
Explanation:
The student's question is about using a least-squares regression line to predict the number of juvenile violent crime arrests in a state, given that 25% of children under age 18 are not in school or in the labor force. In statistics, the least-squares regression line is the best-fitting straight line through a set of data points that minimizes the sum of the squares of the vertical distances (residuals) between the observed values and the values provided by the line.
To make a prediction using the least-squares regression line, you can find the point on the line that corresponds to the given percentage (25% in this case) on the x-axis. You then read or calculate the corresponding value on the y-axis, which would give you the predicted number of juvenile violent crime arrests. This process is a standard application of regression analysis in statistics.
