Two different forecasting techniques, Linear Regression and
Trend-Seasonal, were used to forecast demand for cases of bottled
water. Actual demand and the two sets of forecasts are as
follows.
Predicted Demand
Period Sales Regression Linear regression Trend-Seasonal
1 282 200 290
2 255 210 230
3 262 220 270
4 290 230 210
5 230 240 250
A) Compute the MAD and Bias for each technique.
B) Construct a sentence to describe what the MAD and Bias tell
the average...
Write two paragraphs about the forecasting method of Dynamic
regression model. Discuss how to account for errors from a
regression in an autocorrelation. What are those errors? How can
they occur? Why do they matter? What can be done to deal with those
errors to improve the quality of the forecasting model? Why don’t
forecasters and managers look for or find these errors when using
dynamic regression models?
Identify the tools and techniques available to managers in the
area of forecasting and planning. Discuss how you will use these
tools to forecast sales and prepare a financial plan for your
company?
Discuss three methods of forecasting the future requirements
for demand.
Discuss measures to meet demand for access to medical care in
the future.
Analyze policy proposals to meet the demands identified.
Using forecasting techniques like Delphi method or
survey of intentions, as well as information available in the IBIS
World Industry Report, identify and describe existing and emerging
market needs for chocolate industry
Regression analysis is
an important statistical method for the analysis of business data.
It enables the identification and characterization of relationships
among factors and enables the identification of areas of
significance.
The performance and
interpretation of linear regression analysis are subject to a
variety of pitfalls. Comment on what these pitfalls may be and how
you would avoid them. Use an example if it helps to clarify the
point.
I want to cover Quantitative Forecasting Methods
linear regression
the moving averages
smoothing techniques
How are these used and do they prediction the future
Write the regression equation.
Discuss the statistical significance of the model using the
appropriate regression statistic at a 95% level of confidence.
Discuss the statistical significance of the coefficient for the
independent variable using the appropriate regression statistic at
a 95% level of confidence.
Interpret the coefficient for the independent variable.
What percentage of the observed variation in income is
explained by the model?
Predict the value of a person’s income with 3 children, using
this regression model.
SUMMARY OUTPUT...