Application Guide

328 Lists&Spreadsheet Application
• Sum of the squared data, Gx
2
or Gy
2
• Sample standard deviation, sx = s
n-1
x or sy = s
n-1
y
• Population standard deviation, sx = s
n
x or sy = s
n
y
• X-min or Y-min
• First quartile, Q
1
X or Q
1
Y
• Median
• Third quartile, Q
3
X or Q
3
Y
• X-max or Y-max
• Sum of squared deviations, SSx = G(x Nx)
2
or SSy = G(y Ny)
2
Additional data:
• Sample size for each data set, n
• Gxy
• Correlation coefficient, R.
Linear Regression (mx+b) (LinRegMx)
Fits the model equation y=ax+b to the data using a least-squares fit. It displays values
for m (slope) and b (y-intercept).
Linear Regression (a+bx) (LinRegBx)
Fits the model equation y=a+bx to the data using a least-squares fit. It displays values
for a (y-intercept), b (slope), r
2
, and r.
Median-Median Line (MedMed)
Fits the model equation y=mx+b to the data using the median-median line (resistant
line) technique, calculating the summary points x1, y1, x2, y2, x3, and y3.
Median-MedianLine displays values for m (slope) and b (y-intercept).
Quadratic Regression (QuadReg)
Fits the second-degree polynomial y=ax
2
+bx+c to the data. It displays values for a, b, c,
and R
2
. For three data points, the equation is a polynomial fit; for four or more, it is a
polynomial regression. At least three data points are required.