Low-income students tend to have lower attendance rates and lower math test scores than their middle/upper income peers. Would raising their attendance close the achievement gap? To explore this possibility, a random sample was collected of students in a local school district. For each student, data was collected on their attendance rate (percent of school days attended) and raw test scores on the Algebra 1 state exam. The superintendent of the district asks: “If a student meets our minimum attendance goal (87%), what would their predicted test score be?” In order to answer this question, we first need to find the equation of the least squares regression line. This involves multiple parts, including the slope and intercept. Percent Attendance (x) STAAR Algebra 1 Raw Score (y) 95 45 82 49 61 37 Find the slope for the equation of the least squares regression line: A. 0.5. B. 0.267 C. 1 Find the intercept for the equation of the least squares regression line: A. 0. B.-2.5 C. 22.463
Low-income students tend to have lower attendance rates and lower math test scores than their middle/upper income peers. Would raising their attendance close the achievement gap? To explore this possibility, a random sample was collected of students in a local school district. For each student, data was collected on their attendance rate (percent of school days attended) and raw test scores on the Algebra 1 state exam. The superintendent of the district asks: “If a student meets our minimum attendance goal (87%), what would their predicted test score be?” In order to answer this question, we first need to find the equation of the least squares regression line. This involves multiple parts, including the slope and intercept.
|
Percent Attendance (x) |
STAAR Algebra 1 Raw Score (y) |
|
95 |
45 |
|
82 |
49 |
|
61 |
37 |
Find the slope for the equation of the least squares regression line: A. 0.5. B. 0.267 C. 1
Find the intercept for the equation of the least squares regression line: A. 0. B.-2.5 C. 22.463
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