# Review Test Submission: Quiz4 Course QMBLC Summer14Test Quiz4 Question 1 Shown

Review Test Submission: Quiz4 Course QMBLC Summer14Test Quiz4 Question 1 Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). The percent of the variability in the prediction of Y that can be attributed to the variable X Regression StatisticsMultiple R 0.7732R Square 0.5978Adjusted R Square 0.5476Standard Error 3.0414Observations 10ANOVA df SS MS F Significance FRegression 1 110 110 11.892 0.009Residual 8 74 9.25 Total 9 184 Coefficients Standard Error t Stat P-valueIntercept 39.222 5.942 6.600 0.000X -0.556 0.161 -3.448 0.009 Question 2 Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). Is this model significant at the 0.05 level? Regression StatisticsMultiple R 0.1347R Square 0.0181Adjusted R Square -0.0574Standard Error 3.384Observations 15ANOVA df SS MS F Significance FRegression 1 2.750 2.75 0.2402 0.6322Residual 13 148.850 11.45 Total 14 151.600 Coefficients Standard Error t Stat p-valueIntercept 8.6 2.2197 3.8744 0.0019X 0.25 0.5101 0.4901 0.6322 Question 3 A regression analysis between sales and price resulted in the following equation Y=50,000 – 8000XThe above equation implies that an Question 4 The actual demand for a product and the forecast for the product are shown below. Calculate the MAD.Observation Actual Demand (A) Forecast (F)1 35 —2 30 353 26 304 34 265 28 346 38 28 Question 5 Below you are given the first two values of a time series. You are also given the first two values of the exponential smoothing forecast.Time Period (t) Time Series Value (Y t) Exponential SmoothingForecast (F t)1 22 222 26 22If the smoothing constant equals .3, then the exponential smoothing forecast for time period three is Question 6 What is the forecast for June based on a three-month weighted moving average applied to the following past demand data and using the weights: .5, .3, and .2 (largest weight is for the most recent data)? Month Demand ForecastJanuary 40 February 45 March 57 April 60 May 75 June 87 Question 7 The following time series shows the number of units of a particular product sold over the past six months. Compute the MSE for the 3-month moving average.Month Units Sold(Thousands)1 82 33 44 55 126 10 Question 8 Given an actual demand of 61, forecast of 58, and an alpha factor of .2, what would the forecast for the next period be using simple exponential smoothing?Review Test Submission: Quiz4 Course QMBLC Summer14Test Quiz4 Question 1 Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). The percent of the variability in the prediction of Y that can be attributed to the variable X Regression StatisticsMultiple R 0.7732R Square 0.5978Adjusted R Square 0.5476Standard Error 3.0414Observations 10ANOVA df SS MS F Significance FRegression 1 110 110 11.892 0.009Residual 8 74 9.25 Total 9 184 Coefficients Standard Error t Stat P-valueIntercept 39.222 5.942 6.600 0.000X -0.556 0.161 -3.448 0.009 Question 2 Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). Is this model significant at the 0.05 level? Regression StatisticsMultiple R 0.1347R Square 0.0181Adjusted R Square -0.0574Standard Error 3.384Observations 15ANOVA df SS MS F Significance FRegression 1 2.750 2.75 0.2402 0.6322Residual 13 148.850 11.45 Total 14 151.600 Coefficients Standard Error t Stat p-valueIntercept 8.6 2.2197 3.8744 0.0019X 0.25 0.5101 0.4901 0.6322 Question 3 A regression analysis between sales and price resulted in the following equation Y=50,000 – 8000XThe above equation implies that an Question 4 The actual demand for a product and the forecast for the product are shown below. Calculate the MAD.Observation Actual Demand (A) Forecast (F)1 35 —2 30 353 26 304 34 265 28 346 38 28 Question 5 Below you are given the first two values of a time series. You are also given the first two values of the exponential smoothing forecast.Time Period (t) Time Series Value (Y t) Exponential SmoothingForecast (F t)1 22 222 26 22If the smoothing constant equals .3, then the exponential smoothing forecast for time period three is Question 6 What is the forecast for June based on a three-month weighted moving average applied to the following past demand data and using the weights: .5, .3, and .2 (largest weight is for the most recent data)? Month Demand ForecastJanuary 40 February 45 March 57 April 60 May 75 June 87 Question 7 The following time series shows the number of units of a particular product sold over the past six months. Compute the MSE for the 3-month moving average.Month Units Sold(Thousands)1 82 33 44 55 126 10 Question 8 Given an actual demand of 61, forecast of 58, and an alpha factor of .2, what would the forecast for the next period be using simple exponential smoothing?

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