Test #4
4-1
1. Slope Intercept Form- An equation of the form y=mx+b, where m is the slope and b is the y-intercept.
2. Constant Functions- A linear function in the form y=b.
4-2
3. Constraint- A condition that a solution must satisfy. Equations can be viewed as constraints in a problem situation. The solutions of the equation meet the constraints of the problem.
4. Linear Extrapolation- The use of a linear equation to predict values that are outside the range of data.
4-3
5. Point-Slope Form- An equation of the form y-y1=m(x-x1), where m is the slope and (x1, y1) is a given point on a nonvertical line.
4-4
6. Parallel Lines- Lines in the same plane that do not intersect and either have the same slope or are vertical.
7. Perpendicular Lines- Lines that intersect to form a right angle.
4-5
8. Bivariate Data- Data with two variables.
9. Scatter Plot- Shows the relationship between a set of data with two variables, graphed as ordered pairs on a coordinate plane.
10. Line of Fit- A line that describes the trend of data in a scatter plot.
11. Linear Interpolation- The use of a linear equation to predict values that are inside the data range.
4-6
12. Best-Fit Line- The line that most closely approximates the data in a scatter plot.
13. Linear Regression- An algorithm to find a precise line of fit for a set of data.
14. Correlations Coefficient- A value that shoes how close data points are to a line.
15. Residual- The difference between an observed y-value and its predicted y-value on a regression line.
16. Median-Fit Line- A type of best-fit line that is calculated using the medians and the coordinates of data points.
4-7
17. Inverse Relation- A set of ordered pairs obtained by exchanging the x-coordinates with the y-coordinates of each ordered pair in a relation.
4-1
1. Slope Intercept Form- An equation of the form y=mx+b, where m is the slope and b is the y-intercept.
2. Constant Functions- A linear function in the form y=b.
4-2
3. Constraint- A condition that a solution must satisfy. Equations can be viewed as constraints in a problem situation. The solutions of the equation meet the constraints of the problem.
4. Linear Extrapolation- The use of a linear equation to predict values that are outside the range of data.
4-3
5. Point-Slope Form- An equation of the form y-y1=m(x-x1), where m is the slope and (x1, y1) is a given point on a nonvertical line.
4-4
6. Parallel Lines- Lines in the same plane that do not intersect and either have the same slope or are vertical.
7. Perpendicular Lines- Lines that intersect to form a right angle.
4-5
8. Bivariate Data- Data with two variables.
9. Scatter Plot- Shows the relationship between a set of data with two variables, graphed as ordered pairs on a coordinate plane.
10. Line of Fit- A line that describes the trend of data in a scatter plot.
11. Linear Interpolation- The use of a linear equation to predict values that are inside the data range.
4-6
12. Best-Fit Line- The line that most closely approximates the data in a scatter plot.
13. Linear Regression- An algorithm to find a precise line of fit for a set of data.
14. Correlations Coefficient- A value that shoes how close data points are to a line.
15. Residual- The difference between an observed y-value and its predicted y-value on a regression line.
16. Median-Fit Line- A type of best-fit line that is calculated using the medians and the coordinates of data points.
4-7
17. Inverse Relation- A set of ordered pairs obtained by exchanging the x-coordinates with the y-coordinates of each ordered pair in a relation.