trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components?   The model can be additive or multiplicative. When we do use an additive model? When do we use a multiplicative model?   We have different ways of showing and projecting trends in a time series. the three most common are moving averages, exponential smoothing and our new friend regression analysis. How might any of these be used? Have you seen any in use?

The number of auto accidents in Athens, Ohio is related to the regional number of regisgtered automobiles in thousands (X1) alcholic beverage sales in $10,000 (X2) and rainfall in inches (X3). Furthermore the regression formula has been calculated as:             y=a+b1X1+b2x2+b3X3 where  y= number of automobile accidents a=  8.0  b1= 3.5 b2=5.0 b3= 2.4  For the given values of X1,X2, and X3, the expected number of accidents will be ( round your responses to one decimal place)                 X1           X2              X3            # of accidents                  6.0           7.0             0.0               [__]

Develop a forecast for the next month using a four-month moving average method. Use the Excel Functions SLOPE and INTERCEPT to write the linear regression prediction equation with Months as the independent variable and sales as the dependent variable. Use the prediction equation to estimate the number of sales in month 9.

The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4​ months:                                                                                                       Month Jan Feb Mar Apr Number of Accidents 30 48 70 90 Part 2 Using the least-squares regression LOADING... ​method, the trend equation for forecasting is ​(round your responses to two decimal ​places)​:   y ​= enter your response here ​+ enter your response here x   Y=?+?x

A company wants to generate a forecast for unit demand for year 2017 using exponential smoothing. The actual demand in year 2016 was 120. The forecast demand in year 2016 was 110. Using this data and a smoothing constant alpha of 0.1, which of the following is the resulting year 2017 forecast value?

What is time series decomposition?  Why would a forecaster choose this method versus some of the other methods we've learned in class? In your answer, please make sure to define the components of a time series.

The monthly sales for Yazici Batteries, Inc., were as follows: Jan Feb Mar Apr May Jun Jul Aug Sept Oct 21 23 17 14 11 16 16 18 Nov Dec 20 20 20 24 Month Sales This exercise contains only parts b and c b) The forecast for the next month (Jan) using the naive method=sales (round your response to a whole number). The forecast for the next period (Jan) using a 3-month moving average approach = sales (round your response to two decimal places). The forecast for the next period (Jan) using a 6-month weighted average with weights of 0.10, 0.10, 0.10, 0.20, 0.20, and 0.30, where the heaviest weights are applied to the most recent month= sales (round your response to one decimal place) Using exponential smoothing with a = 0.30 and a September forecast of 21.00, the forecast for the next period (Jan) = sales (round your response to two decimal places). Using a method of trend projection, the forecast for the next month (Jan) = sales (round your response to two decimal places). c) The method…