WGU C955 Applied
Probability and Statistics |
Study Guide, Practice
Questions & Exam
Review
|Guaranteed success|
, Correlation Coefficient (r) A number from -1 to +1 that measures the strength and direction of a LINEAR
relationship between two variables. Near -1 or +1 = strong. Near 0 = weak.
Weak Correlation Range r values between -0.3 and 0.3
Moderate Correlation Range r values between -0.7 and -0.3, OR between 0.3 and 0.7
Strong Correlation Range r values between -1 and -0.7, OR between 0.7 and 1
Positive Correlation As the explanatory variable (x) increases, the response variable (y) also
increases. Scatterplot trends upward left to right.
Negative Correlation As the explanatory variable (x) increases, the response variable (y) decreases.
Scatterplot trends downward left to right.
Regression Equation (slope-intercept form) y = mx + b. m = slope (change in y per 1-unit increase in x). b = y-intercept
(predicted y when x = 0).
Slope in Regression For every 1-unit increase in the explanatory variable (x), the response variable
(y) is predicted to increase (or decrease if negative) by m units.
Y-intercept in Regression The predicted value of y when x = 0. It is the starting point of the regression
line.
Explanatory Variable The independent variable (x-axis). It is used to explain or predict changes in the
response variable.
Response Variable The dependent variable (y-axis). Its value "responds" to changes in the
explanatory variable.
Regression Line (Line of Best Fit) The line that minimizes the total distance between each data point and the line
itself. Found using the least squares method.
Linear Interpolation Using the regression equation to estimate a value WITHIN the range of known
data points.
Probability and Statistics |
Study Guide, Practice
Questions & Exam
Review
|Guaranteed success|
, Correlation Coefficient (r) A number from -1 to +1 that measures the strength and direction of a LINEAR
relationship between two variables. Near -1 or +1 = strong. Near 0 = weak.
Weak Correlation Range r values between -0.3 and 0.3
Moderate Correlation Range r values between -0.7 and -0.3, OR between 0.3 and 0.7
Strong Correlation Range r values between -1 and -0.7, OR between 0.7 and 1
Positive Correlation As the explanatory variable (x) increases, the response variable (y) also
increases. Scatterplot trends upward left to right.
Negative Correlation As the explanatory variable (x) increases, the response variable (y) decreases.
Scatterplot trends downward left to right.
Regression Equation (slope-intercept form) y = mx + b. m = slope (change in y per 1-unit increase in x). b = y-intercept
(predicted y when x = 0).
Slope in Regression For every 1-unit increase in the explanatory variable (x), the response variable
(y) is predicted to increase (or decrease if negative) by m units.
Y-intercept in Regression The predicted value of y when x = 0. It is the starting point of the regression
line.
Explanatory Variable The independent variable (x-axis). It is used to explain or predict changes in the
response variable.
Response Variable The dependent variable (y-axis). Its value "responds" to changes in the
explanatory variable.
Regression Line (Line of Best Fit) The line that minimizes the total distance between each data point and the line
itself. Found using the least squares method.
Linear Interpolation Using the regression equation to estimate a value WITHIN the range of known
data points.
