QA 1,3-4 Questions T/F

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A mathematical model shows the relationship between quantifiable and non-quantifiable information.

False

A parameter is a measurable quantity that may vary or is subject to change.

False

All problems can be solved by considering only the quantitative issues.

False

Descriptive Analytics is aimed at forecasting future outcomes based on patterns in the past data.

False

Revenue is calculated by subtracting expenses from profit.

False

A scatter diagram for a time series may be plotted on a two-dimensional graph with the horizontal axis representing the variable to be forecast (such as sales).

False - Variable to be forecasted y-axis (vertical)

Four components of time series are trend, moving average, exponential smoothing, and seasonality.

False - trend, seasonal, cyclical, random

An exponential forecasting method is a time series forecasting method.

True

An exponential method is a time series forecasting method.

True

Bias is the average error of a forecast model.

True

One problem in using a quantitative model is that the necessary data may be unavailable.

True

Scatter diagrams can be useful in spotting trends or cycles in data over time.

True

The fewer the periods over which one takes a moving average, the more accurately the resulting forecast mirrors the actual data of the most recent time periods.

True

The most common quantitative causal model is regression analysis.

True

The trend component of a time series captures whether the level of the variable of interest is generally increasing or decreasing over time.

True

When a problem is difficult to quantify, it may be necessary to develop unspecific objectives.

False

A sensitivity analysis allows a manager to answer the "what if" questions.

True

Time series models enable the forecaster to include specific representations of various qualitative and quantitative factors.

False

The three categories of forecasting models are time series, quantitative, and qualitative.

False - qualitative models, time-series methods, casual methods

Model variables can be controllable or uncontrollable.

True

Models can help us analyze a problem and sell a decision to those who must implement it.

True


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