Assignment 4-2

Answer in Excel: Consider the data below for the sales of widgets: 1. Using seasonal percentages or seasonal indexes, forecast the sales for each season in year 4, if the annual widgets sales is predicted to be 1500. 2. Develop a regression equation that captures both the trend and seasonality in this data. Use this equation to forecast the sales for each season in year 4. Season Year 1 Year 2 Year 3 Fall 505 240 210 Winter 555 460 365 Spring 400 310 204 Summer 560 450 394

A random sample of 10,000 customers was selected over a six month period. The data provides information on their current status with the bank as well as 12 additional attributes describing their demographic and banking information.  what are the key predictors the bank should be aware of with their customers? Examples are included, but not limited to:Are female customers leaving more than males? Is there indication of customer departures associated with specific countries?Is there evidence of salary associated departures? what is an appropiate marketing strategy to attract and retain long term customers

For the E-Commerce Retail Sales (Million$) data given in the table below, provide estimates from the 1st Quarter (Q1) of 2016 to the 3rd Quarter (Q3) of 2017 by using two models: 1) Single Exponential Smoothing with α=0.3 2) Moving Average with k=2. Calculate MAPE for each model. Quarter Year Actual Q1 2016 86802 Q2 2016 92004 Q3 2016 93795 Q4 2016 124651 Q1 2017 99491 Q2 2017 106590 Q3 2017 108291   Compare two models above (Single Exponential Smoothing and Moving Average) based on their accuracies. Which forecasting method appears to be better? Using the model you choose, provide forecast for the 4th Quarter (Q4) of 2017. Assuming that this model is overestimating, find the actual value of the Q4 of 2017 based on MAPE value.   Some residual graphs from the first forecast model (including wider range of E-Commerce Retail Sales data) are given below. What do these graphs tell about the model? Explain each graph.

Q2: An economist who estimated the Keynesian money demand function in logarithmic form using data from Sri Lankan economy, obtained the graph on the left by using predicted and actual money demand. While the model was very successful in predicting money demand until 2010 (small forecast errors), it predicts a consistently higher money demand than actually occurred since then (growing forecast errors each period). 48 Ln(M) 4.75 4.7 4.65 4.6 4.55 Actual 4.5 Predicted ...... 4.45 Help this economist who has trouble explaining this situation, even if you do not know anything about the economy in question. Can you answer this question with details please? 6toz Stor

The table below shows the quarterly sales of television set (in thousands) in an electrical appliance shop in years 2017-2019. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 2017 4.8 4.1 6.0 6.5 2018 5.8 5.2 6.8 7.4 2019 6. 5.6 7,5 7.8 (a) Describe the trend and seasonal variation of the sales of television set by referring to the following time series plot. (In a short paragraph of around 30 words.) Sales of Television Set (1000s) 2 3 5 8 9 10 11 12 Time: (2017 Quarter 1 to 2019 Quarter 4) (b) Calculate the seasonal variation for Quarter 1, Quarter 2, Quarter 3, and Quarter 4 respectively by using the calculated 4-quarter moving average as below. Year Quarter Sales Centered Moving (1000) Average (1000) 2017 5.475 2017 4 6.5 5.7375 2018 1 5.8 5.975 2018 2 5.2 6.1875 2018 3 6.8 6.325 2018 7.4 6.4 2019 1 6 6.5375 2019 2 5.6 6.675 TTTT"

please help me understand the problem

Sales of​ Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years​ (see table​ below).                                                      Year Sales 1 455 2 510 3 518 4 570 5 590 ​a) Forecasted sales for year 6 using the trend projection​ (linear regression) method are nothing sales ​(round your response to one decimal​ place)

The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OF MERLOT WINE 1 270 2 356 3 398 4 456 5 358 6 500 7 410 8 376 Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8. Note: Round your intermediate calculations and final answer to the nearest whole number.

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Solve the problem using the answer sheet (Problem 1) SOLVE STEP BY STEP PLEASE

Corporate triple-A bond interest rates for 12 consecutive months are as follows. 9.5 9.4 9.5 9.7 9.8 9.8 9.9 10.6 10.0 9.8 9.7 9.7 (a) Construct a time series plot. What type of pattern exists in the data? The data appear to follow a trend pattern.The data appear to follow a horizontal pattern.    The data appear to follow a seasonal pattern.The data appear to follow a cyclical pattern. (b) Develop three-month and four-month moving averages for this time series. (Round your answers to two decimal places.) Month Time SeriesValue 3-Month MovingAverage Forecast 4-Month MovingAverage Forecast 1 9.5     2 9.4     3 9.5     4 9.7     5 9.8     6 9.8     7 9.9     8 10.6     9 10.0     10 9.8     11 9.7     12 9.7     Does the three-month or four-month moving average provide the better forecasts based on MSE? Explain. The four-month moving average provides more accurate forecasts, because its MSE is smaller than that of the three-month moving…

The following table shows 6 students' tea consumption and their income. Find the coefficient for the impact of income on tea consumption using simple linear regression. Observations Tea Consumption Income 90 1 2 3 4 5 сл 6 18 14 20 25 8 12 100 80 60 100 110

The number of patients coming to the Healthy Start Maternity clinic has been increasing steadilyover the past eight months. You are provided with some historical data as follows: Month       Clinic attendance                  (in thousands)1                  3.42                  3.93                  4.54                  5.05                  5.86                  5.97                  6.58                  6.7 a. Identify and give a brief explanation of the:i. Dependent variableii. Independent variable  b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:i. Derive the values for the intercept and slope. ii. Derive the linear regression equation. iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.

Given the following data, use least-squares regression to derive a trend equation: Period Demand where y Demand and x = Period. 1 10 2 12 3 5 4 13 5 12 6 11 D The least-squares regression equation that shows the best relationship between demand and period is (round your responses to two decimal places):

Sales of Volkswagens have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Year Sales 1 450 2 495 TIT 3 520 4 575 5 580 sales (round your response to one decimal place). a) Forecasted sales for year 6 using the trend projection (linear regression) method are