FIN Modeling Midterm Ch 1-3

If the smoothing constant of .3 is used, what is the exponentially smoothed forecast for period 4? (LOOK at pic) A) 112.6 B) 104.4 C) 106.6 D) 115.0 E) 103.0

106.6

A random sample of employee files is drawn revealing an average of 2.8 overtime hours worked per week with a standard deviation of .7, the sample size is 500. The resulting 90% confidence interval is A) 2.75 to 2.85 B) None of the options are correct C) 2.6 to 3.0 D) 2.1 to 3.5 E) 2.6 to 3.5

2.75 to 2.85

The data above represents the total houses sold in thousands of units per month through December of 2004. Use an appropriate naïve model to forecast January 2005 sales. A) 80 B) 94 C) 76 D) 72

89

In the table above. Total houses sold in the United States are forecasted by what method (look at pics on phone) A) A simple smoothing model B) A naive model C) A modified model with a lag of 12 D) A modified model with a lag of 4

A m odified naive model with a lag of 12

Which of the following is incorrect? A) Forecast errors should not be discussed since most people know that forecasting is an inexact science. B) None of the options are correct. C) You should tailor your presentation to the sophistication of the audience to maximize credibility in the forecast process. D) The forecaster should be able to defend why a particular model or procedure has been chosen. E) Forecast errors should be discussed in an objective manner to maximize management's confidence in the forecast process.

A) Forecast errors should not be discussed since most people know that forecasting is an inexact science.

Which of the following is not an attribute of a normal probability distribution? A) Most observations cluster around zero. B) The distribution is completely determined by the mean and variance. C) It is symmetrical about the mean. D) Most observations cluster around the mean. E) All of the options are correct.

A) Most observations cluster around zero.

Which of the following is not a measure of central tendency in a population? A) Range. B) Mean. C) Median. D) Mode.

A) Range.

In the table shown above, the root mean square error calculated is (see phone for pic) A) an "in sample" RMSE. B) an inappropriate measure to use because of the seasonality of the data. C) an "out of sample" RMSE. D) a measure of "accuracy".

A) an "in sample" RMSE.

Correlation coefficients may range in value A) from −1 to +1. B) from zero to four. C) from zero to 100 percent. D) from zero to one.

A) from −1 to +1.

Accuracy refers to A) how well the model works in the forecast horizon. B) the accuracy of the seasonal component of a forecasting model. C) how accurate the measures of central tendency will be. D) how well the model works retrospectively.

A) how well the model works in the forecast horizon.

An unbiased model A) is one that does not consistently over-estimate or under-estimate the true value of a parameter B) is one which contains no independent variable; it depends solely on time-series pattern recognition C) is one that consistently produces estimates with the smallest RMSE D) is one made up by a team of forecasters

A) is one that does not consistently over-estimate or under-estimate the true value of a parameter

Consider the following equation: (Look at phone) This equation represents A) the calculated Pearson product-moment correlation coefficient. B) the calculated standard deviation. C) a calculated t-statistic. D) the calculated Z-statistic.

A) the calculated Pearson product-moment correlation coefficient.

The notion of a product life cycle can be applied to A) A product form B) A product Class C) brand D) All of the options are correct

All of the options are correct

The smoothing constant in the exponential smoothing model: A) Completely determines the weight structure in exponential smoothing B) All of the options are correct C) Cannot be equal to 0 or 1 D) Can be interpreted as the revision of the period's forecast to today's forecast error E) Must be between o and 1

All of the options are correct

Which of the following measures of forecast fit may correctly be used to compare different forecast models of a given data series? A) Root Mean Squared Error B) Mean Absolute Error C) All of the options are correct. D)Theil's U

All of the options are correct

A random sample of bolts is taken from inventory, and their lengths are measured. The average length in the sample is 5.3 inches with a standard deviation of .2 inches. The sample size was 50. A 95% confidence interval for the unknown population mean is: A) 5.3 inches. B) 5.3 inches plus or minus .056. C) None of the options are correct. D) 4.784 to 5.816 inches. E) 4.9 to 5.7 inches.

B) 5.3 inches plus or minus .056.

In the Adaptive-Response-Rate Single Exponential Smoothing model, the smoothing parameter A) is the ratio of two smoothed error measures. B) All of the options are correct. C) is determined by the ratio of the absolute value of the smoothed error divided by the absolute smoothed error. D) varies from period to period. E) is not a constant.

B) All of the options are correct.

In Chapter One of the textbook, the following statement appears: "Throughout the text, you may find some situations that we show do not match exactly with the ForecastX results." What is the reason given for making this statement? A) All of the options are correct. B) ForecastX invokes proprietary alterations from the standard calculations. C)ForecastX uses a "stack procedure" in its calculations. D) ForecastX, and other software packages, will always have rounding errors.

B) ForecastX invokes proprietary alterations from the standard calculations.

Which of the following is not a descriptive statistic? A) Expected value. B) None of the options are correct. C) Variance. D) Mean. E) Range.

B) None of the options are correct.

Which of the following is not considered a smoothing model? A) Exponential smoothing. B) None of the options are correct. C) Moving averages. D) Adaptive-Response-Rate Single Exponential Smoothing. E) Naïve.

B) None of the options are correct.

What methods seem suited to forecasting new-product sales? A) Extrapolative methods B) Subjective or judgmental methods C) Inductive methods D) Time series methods

B) Subjective or judgmental methods

In the Winters model shown above, index 1 refers to calendar month 1 in the data. ( see phone) A) Thus, calendar month 3 is a below average month. B) Thus, calendar month 3 is an above average month. C) Thus, calendar month 3 is an average month. D) Nothing can be deduced about calendar month 3.

B) Thus, calendar month 3 is an above average month.

The diagram immediately above represents (see phone for pics) A) a normal distribution B) a product life cycle. C) the pre-introductory product development stage. D)a Student's t-test distribution. E) the purchase intentions of hypothetical individuals.

B) a product life cycle

The correlation coefficient is also called A) Theil's U. B) the Pearson product-moment correlation coefficient. C) the autocorrelation coefficient. D) the variance.

B) the Pearson product-moment correlation coefficient.

When running a hypothesis test, the process begins by setting up two hypotheses, A) the theoretical hypothesis and the statistical hypothesis. B) the null hypothesis and the alternative hypothesis. C)the average hypothesis and the mean hypothesis. D) Pearson's hypothesis and the null hypothesis.

B) the null hypothesis and the alternative hypothesis.

PLC was used in the first chapter to represent A) the principle of linear correlation. B) the product life cycle. C) the probability of limited consumption. D) None of the options are correct. E) the positive long-term probability.

B) the product life cycle.

The Gompertz model A) results in an "L-shaped" curve. B) was originally used to test for mortality of fruit flies. C) cannot be used to forecast the sales of a new product. D) is the inverse of the Logistics model.

B) was originally used to test for mortality of fruit flies.

Which of the following statements about any moving-averages series is correct? A) Such a series will anticipate or prolong changes in the original data and, thus, show a different timing of turning points. B) Such a series will be extremely sensitive to unusually large or small values in the time series, as any average is bound to be. C) All are correct. D) A moving-averages series can lie consistently above or below the original data, namely, when they are growing or declining exponentially.

C) All are correct.

In using moving-average smoothing to generate forecasts, a three-month moving average will be preferred to a six-month moving average A) if it has a lower mean-squared error. B) if we have very little data to work with. C) All of the options are correct. D) if the true data cycle is three months. E) if it has a lower RMSE.

C) All of the options are correct.

Which of the following is a factor in the decision to use exponential smoothing rather than moving-average smoothing to forecast a given time series? A) Amount of data available. B) None of the options are correct. C) Importance of recent past versus distant past. D) Expertise of the forecast manager. E) Forecast horizon.

C) Importance of recent past versus distant past.

Which of the following measures of forecast fit can correctly be used to compare "goodness of fit" across different sized random variables? A) None of the options are correct. B) the Durbin Watson statistic C) Mean Absolute Percentage Error D) Mean Percentage Error E) Mean Error

C) Mean Absolute Percentage Error

You are given a time series of sales with 10 observations. You construct forecasts according to the last period's actual level of sales plus the most recent observed change in sales. How many data points will be lost in the forecast process relative to the original data series? A) One B) None of the options are correct C) Two D) Zero E) Three

C) Two

In running an exponential smoothing model, the following results were obtained: The Seasonal value listed above (in Smoothing 3) indicates that the model: ( SEE PIC) A) is probably unreliable for forecasting. B) exhibits a rather high degree of trend. C) exhibits a rather high degree of seasonality. D) has a very high level smoothing constant. E) None of the options are correct.

C) exhibits a rather high degree of seasonality.

If the correlation between body weight and annual income were high and positive, we could conclude that A) high incomes cause people to gain weight. B) high income people tend to spend a greater proportion of their income on food than low income people, on average. C) high income people tend to be heavier than low income people, on average. D) high incomes cause people to eat more food. E) low incomes cause people to eat less food.

C) high income people tend to be heavier than low income people, on average.

When using growth curves such as the Gompertz model or the Logistics model, A) it is necessary to have a large data set. B) it does not matter which model is selected; they are equivalent. C) it is customary to specify a saturation point. D) only short term forecasts are possible.

C) it is customary to specify a saturation point.

In the growth model Audit Trail shown above, a Gompertz Curve was probably selected because ( see pic) A) the trend was nonlinear. B) a "bell shaped" function was expected. C) it was harder to achieve constant improvement as the maximum value was approached. D) it was easier to achieve constant improvement as the maximum value was approached.

C) it was harder to achieve constant improvement as the maximum value was approached.

In order to conduct a correlation analysis, the collected data must be A) All of the options are correct. B) highly correlated C) numerical D) related to the real world E) constructed of categories

C) numerical

Which of the following would not be an appropriate use of forecast errors to assess the fit of a particular forecasting model? A) Examine the average absolute value of the errors. B) None of the options are correct. C) Examine a time series plot of the errors and look for a pattern. D) Examine the average level of the errors. E) Examine the average squared value of the errors.

D) Examine the average level of the errors.

Progressive Insurance Company was cited as being a firm that employed "Industrial Strength Forecasting." In doing so, they collected data on motorcycle riders, their ages, their accident history, their educational level and their credit scores. What did Progressive forecast with this data? A) The likelihood that a motorcycle rider would pay their premium B) The probability that payment would be made on time to Progressive C) The price different motorcycle riders would be willing to pay for insurance D) The risk exhibited by different motorcycle riders

D) The risk exhibited by different motorcycle riders

Consider the ForecastX printout above. This is the forecast for a manufactured product. A) This is a Simple Smoothing model. B) This is a Holt's Smoothing model. C) This is a Winter's Exponential Smoothing model. D) This is an Event model.

D) This is an Event model.

A cyclical pattern A) is a long term change in the level of the data. B) contains the fluctuations that are not part of the other three components. C) occurs in a time series when there is a regular variation in the level of the data that repeats itself at the same time each year. D) is represented by wavelike upward and downward movements of the data around the long-term trend.

D) is represented by wavelike upward and downward movements of the data around the long-term trend.

Stationarity refers to A) a method of forecast optimization. B) the size of variances of the model's estimates. C) None of the options are correct. D) lack of trend in a given time series. E) the size of the RMSE of a forecasting model.

D) lack of trend in a given time series.

The Department of Energy used the Bass model to forecast the adoption of solar batteries. In order to select p and q values, A) they set the qbar (or maximum) value and let the software B) optimize the p and q. C) they used a jury of executive opinion technique. D) they used a survey of home builders. E) they selected p and q values of a similar, but older, product.

D) they used a survey of home builders.

Growth models like those used in ForecastX usually model situations well where a process grows A) at a more or less constant rate. B) in a linear fashion. C) at an exponential rate. D) until reaching saturation.

D) until reaching saturation.

How many parameters must the forecaster (or the software) set using Winter's exponential smoothing? A) None of the options are correct. B) 1. C) 0. D) 2. E) 3.

E) 3.

Holt's model accounts for any growth factor present in a time series by A) smoothing the most recent trend by last period's smoothed trend. B) use of a linear trend. C) using simple exponential smoothing to estimate a trend factor that is then combined in a linear fashion with the level forecast. D) adding trend estimates to level forecasts. E) All of the options are correct.

E) All of the options are correct.

Which of the following points about supply chain management is incorrect? A) Collaborative forecasting systems across the supply chain are needed. B) If you get the forecast right, you have the potential to get everything else right in the supply chain. C) Forecasts are required at each step in the supply chain. D) Forecasts of sales are required for partners in the supply chain. E) None of the options are incorrect.

E) None of the options are incorrect.

If we were to know the true population correlation, confidence intervals for the population correlation can be constructed using the ____ distribution. A) T distribution B) F Distribution C) Chi-square distribution D) All of the options are correct E) standard normal distribution

E) Standard normal distribution

Which of the following methods is not useful for forecasting sales of a new product? A) Consumer Surveys B) All of the options are correct. C) Delphi Method D) Test market results E) Time series techniques requiring lots of historical data

E) Time series techniques requiring lots of historical data

Suppose you are attempting to forecast a variable that is independent over time such as stock rates of return. A potential candidate-forecasting model is A) the Jury of Executive Opinion. B) None of the options are correct. C) last period's actual rate of return plus some proportion of the most recently observed rate of change in the series. D) the Delphi Method. E) last period's actual rate of return.

E) last period's actual rate of return.

The t-Distribution (also called the Student's t-Distribution) A) resembles a Chi-Square distribution. B) resembles a normal distribution. C) resembles Theil's Distribution. D) resembles a Gaussian distribution. E) resembles both a normal and a Gaussian distribution.

E) resembles both a normal and a Gaussian distribution.

Based upon ten years of monthly data, the monthly rate of return for the Dow Jones 30 composite stock portfolio was normal distributed with mean .0084 and variance .0014. What is the probability, that in any given method, we observe a rate of return on the DOW above 10 percent? A) Not enough information is provided to answer the question. B) Three percent C) Less than one percent D) Two percent

Less than one percent

Qualitative or subjective forecasting methods include A) The bass model B) The naive model C) Surveys of customers D) Exponential smoothing

Surveys of customers