Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2. $$\begin{array} { | c | c | }
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-Using the data, determine the value of the simple moving average root mean square error.
A) 0.21
B) 14.39
C) 20.12
D) 207.13

Question

Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2. $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-Using the data, determine the value of the simple moving average root mean square error.
A) 0.21
B) 14.39
C) 20.12
D) 207.13

Quizplus · Accepted Answer

The simple moving average (SMA) for k=2 is calculated for each pair of weeks, then the root mean square error (RMSE) is determined based on the actual values and the SMA values. The SMA values for weeks 2 through 6 are (88+44)/2=66, (44+54)/2=49, (54+65)/2=59.5, (65+72)/2=68.5, and (72+85)/2=78.5, respectively. The differences between actual values and SMA values are squared, summed, and then divided by the number of observations (5 in this case, since the first week doesn't have a preceding week to form a pair for SMA calculation), and the square root of this result gives the RMSE, which is approximately 14.39.

Use the Data Given Below to Answer the Following Questions)