APPLIED DECISION METHODS CLASS; MOD4 - Essay Example

Assignment Answers Below are explanations to the computed questions attached in Microsoft Excel. Q.30) Do schools with higher SAT scores charge morein tuition and fees?Not really. Despite the fact that a fair correlation coefficientas obtained from the computed results of 0.470082 between the variables, the significance F/the overall validity of the model is close to 0.05. This renders the model to be statistically invalid. Consequently, the variables are not statistically significant due to the same reason.ii)Are private schoolsmore expensive than public schools when the SAT scores are taken into consideration?

This is not the case. The R-Squared is obtained as 0.220978. This is a weak number and it implies that 22% of variability in the tuition prices to be charged both in the private and public schools will be explained by the SAT scores. As such, this can’t exactly be used as a basis on determining the overall relation betweenthe cost charged and the SATs scored. The model as from the computations is invalid meaning it can’t be used to assess the question given Q.31) Develop a regression model to predict the total number of victories based on the payroll of a team.

Discuss how accurate this model is.As computed, the correlation coefficient of the created model is a weak positive number of 0.17577. Thisshows a weakrelationship of the model. The overall significance of the model should be less than 0.05. In our case, our model gives a value of 0.547796. This shows the model isn’t statistically valid rendering our model inaccurate. Then again, the variability of the dependent variableas explained by the independent variable is 0.030895 which yields a percentage of 3.

0895 which is a very weak number. Consequently, the variables aren’t statistically significant as they are close to 0.05. (0.049008). ii) Use the model to predict the number of victories for a team with a payroll of 79 million $.This can be estimated by multiplying the payroll with the strength of the relationship described by the model. We subtract 17.577% from 100% to get 82.423%.We then multiply this by the payroll spent by the team that is 82.433%/100% * 79 and we obtain roughly about 65 victories. Q.25) Using a moving average with three periods, determine the demand for vacuum cleaners for next February.

From the model output, the forecast for February is13.6666667. ii) Using a weighted moving average 3 periods, determine demand for vacuum cleaners.The forecast as obtained from the model for February is 13.166667.iii) Evaluate the accuracy of each of the model.Despite the moving average being an accurate method of forecasting sales, the weighted moving average is even more accurate as one can weigh the more recent periods a little heavier than the older periods.iv)What other methods might R.

Lowenthal consider in forecasting sales?He may use methods such as:Multiple regressionExponential smoothingMultiplicative Season ModelRegression Projector.References:1) Levie, Robert. Advanced Excel for scientific data analysis. Oxford New York: Oxford University Press, 2004. Print.