Final Quiz

Question 1

The problem with regular spreadsheets?

Answer 1

This results in a static, or deterministic, result that might be unrepresentative of the range of possible outcomes.

Question 2

Simulation with Crystal Ball?

Answer 2

Use ranges as inputs  thousands of outcomes with associated probabilities
Easy to analyze and communicate

Question 3

What is Monte Carlo Simulation?

Answer 3

A quick, inexpensive way to acquire the knowledge that is usually gained through experience.

Question 4

Who adopted the Monte Carlo Simulation?

Answer 4

The method was adopted and improved by John von Neumann and Stanislaw Ulam for simulations of the atomic bomb during the Manhattan Project. Because the method is based on random chance, it was named after a gambling resort of Monte Carlo (e.g. roulette wheels can be seen as devices for generating uncertain or random events).

Question 5

Simulation model?

Answer 5

Mathematical model that mimics the operation of a real life system…

Simulation models are often used to analyze a decision under risk, when the behavior of one or more factors is not known with certainty.

Question 6

Forecasting methods can be classified as?

Answer 6

qualitative or quantitative.

Question 7

Qualitative methods generally involve?

Answer 7

The use of expert judgment to develop forecasts.

Question 8

Quantitative forecasting methods can be used when?

Answer 8

past information about the variable being forecast is available,

the information can be quantified, and

it is reasonable to assume that the pattern of the past will continue into the future.

Question 9

A time series is?

Answer 9

a set of observations measured at successive points in time or over successive periods of time.

Question 10

If the historical data used are restricted to past values of the series that we are trying to forecast, the procedure is called?

Answer 10

a time series method.

Question 11

If the historical data used involve other time series that are believed to be related to the time series that we are trying to forecast, the procedure is called a?

Answer 11

causal method.

Question 12

The objective of time series analysis is?

Answer 12

to discover a pattern in the historical data or time series and then extrapolate the pattern into the future.

Question 13

A time series plot is?

Answer 13

a graphical presentation of the relationship between time and the time series variable.

Question 14

Now we discuss three forecasting methods that are appropriate for a time series with a horizontal pattern:

Answer 14

Exponential Smoothing. Moving Averages

Weighted Moving Averages

Question 15

What are the three smoothing methods most appropriate for?

Answer 15

short-range forecasts.

Question 16

Why is the term moving used?

Answer 16

because every time a new observation becomes available for the time series, it replaces the oldest observation in the equation.

Question 17

Exponential Smoothing?

Answer 17

The exponential smoothing forecast is a weighted average of all the observations in the time series

Question 18

Curve fitting minimizes?

Answer 18

the sum of squared error between the observed and fitted time series data where the model is a trend line.

Question 19

We build a nonlinear optimization model to?

Answer 19

find the best values for the intercept and slope of the trend line.

Question 20

Regression?

Answer 20

• a forecasting technique that measures the relationship of one variable to one or more other variables.

Question 21

When a regression model involves two or more independent (predictor) variables?

Answer 21

the constant (intercept) is an estimate of the value of the dependent variable when all of the independent variables are equal to zero

Question 22

SIMPLE REGRESSION?

Answer 22

The simplest form of regression is linear regression, which we used to develop a linear trend forecast (time period t was used to predict time series values, e.g. sales)

Question 23

R^2 definition?

Answer 23

An alternative way of defining R2 is as the square of the correlation between the values of yest and the true values (y) of the dependent variable.

Question 24

Multiple regression?

Answer 24

reflects the relationship between a dependent variable and two or more independent (predictor) variables.

Question 25

Multicolinearity?

Answer 25

happens when two or more of the independent (predictor) variables considered in regression model are correlated with each other .