Regression Basics
The dependent variable in regression is also known as this.
(What is the response variable or Y variable?)
This coefficient ranges from -1 to 1 and measures the strength of a linear relationship.
(What is the correlation coefficient?)
What is the formula for a line?
(What is y=mx+b?)
If b₁ = 2.5, this is what happens to Y when X increases by 1 unit.
(What is Y increases by 2.5 units?)
Predicting this business metric based on advertising spend is a common regression application.
(What is sales?)
This term describes how well your regression line fits the data.
(What is goodness of fit?)
This value indicates no linear relationship between variables.
(What is zero?)
This statistic, symbolized as R², ranges from 0 to 1.
(What is the coefficient of determination?)
An R² of 0.75 means this about your model.
(What is 75% of the variation in Y is explained by X?)
This analysis uses regression to determine how sensitive product demand is to price changes.
(What is price elasticity?)
This assumption of linear regression states that the relationship between variables should be linear.
(What is linearity?)
The difference between correlation and this concept is that the latter implies causation.
(What is regression?)
This error term represents the difference between observed and predicted values.
(What is a residual?)
This p-value tells you if a regression coefficient is statistically significant.
(What is the p-value of the t-test?)
Businesses use regression to forecast this time-based data.
(What are trends or time series?)
This plot helps visualize the relationship between two variables before performing regression.
(What is a scatter plot?)
This statistical test determines if a correlation coefficient is significantly different from zero.
(What is a t-test?)
This sum is minimized in ordinary least squares regression.
(What is the sum of squared residuals?)
These bands around a regression line show prediction uncertainty.
(What are confidence intervals?)
This business function uses regression to optimize inventory levels.
(What is supply chain management?)
This problem occurs when independent variables are highly correlated with each other.
(What is multicollinearity?)
This fallacy occurs when we assume correlation implies this.
(What is causation?)
This test evaluates whether all regression coefficients are simultaneously equal to zero.
(What is the F-test?)
This plot helps identify heteroscedasticity in your regression model.
(What is a residual plot?)
This technique helps businesses determine which factors most influence customer satisfaction.
(What is key driver analysis?)