TB MC Qu. 13-15 Forecasting product demand exclusively...

Forecasting product demand exclusively using multiple possible predictive factors is an example of which analytics technique?

Question

TB MC Qu. 13-15 Forecasting product demand exclusively...

Forecasting product demand exclusively using multiple possible predictive factors is an example of which analytics technique?

BlackTom AI · Accepted Answer

We start by restating the question and options to focus the analysis: Forecasting product demand exclusively using multiple possible predictive factors is an example of which analytics technique?

Option 1: Sensitivity analysis. This approach investigates how the variation in input factors impacts outputs, typically used to understand robustness or identify influential variables, but it does not inherently perform predictive modeling with multiple predictors.

Option 2: Regression. Regression techniques model the relationship between a dependent variable (here, product demand) and one or more independent variables (the predictive factors). When multiple predictors are involved, this is multivariate or multiple regression, which is a standard method for forecasting quantitative outcomes based on several inputs.

Option 3: Time series. Time series analysis focuses on data points collected sequentially over time and emphasizes temporal patterns, seasonality, and trend. While it can forecast demand, it relies on past values of demand itself or time-based features, not necessarily a general set of predictive factors.

Option 4: Classification. Classification assigns observations to discrete categories (e.g., high/low demand, product category) rather than predicting a continuous numeric variable like demand quantity. This is not suited for quantitative demand forecasting in the typical sense.

Putting it together, the task described—forecasting a numeric demand outcome using multiple predictive factors—maps most closely to regression, which directly models a quantitative outcome as a function of several predictors. Sensitivity analysis helps probe effects of input changes but does not construct a predictive model with predictors. Time series emphasizes temporal sequencing rather than a broad set of predictors, and classification is about category labels rather than numeric forecasting. Therefore, regression is the technique that best fits the described scenario.

TB MC Qu. 13-15 Forecasting product demand exclusively... Forecasting product demand exclusively using multiple possible predictive factors is an example of which analytics technique?

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