Final answer:
The relationship where a response variable is uniquely determined by predictor variables is known as deterministic, not stochastic, which includes randomness and unpredictability in the relationship between variables.
Step-by-step explanation:
If the value of the response variable is uniquely determined by the values of the predictor variables, the relationship between the variables is described as deterministic, not stochastic. A deterministic relationship implies a perfect, or near-perfect, correlation between the predictor and response variables. In other words, knowing the value of the predictor variables allows for an exact prediction of the response variable. This is commonly seen in mathematical formulas or physical laws where the output is precisely defined by the input.
In contrast, a stochastic relationship implies randomness or unpredictability within the relationship between variables. In a stochastic model, the outcome for the response variable is not fixed by the predictor variables and can vary due to random errors or inherent randomness in the system. Real-world examples of stochastic processes include stock market fluctuations, weather patterns, and many social science phenomena where predictions are not exact but instead have associated probabilities of occurrence.
In summary, if the response value is uniquely determined by predictor values, we are looking at a deterministic relationship. Whereas, if there is randomness or unpredictability in the prediction of the response value, then the relationship is stochastic.