SCENARIO 16-13
Given Below Is the Monthly Time Series Data

question 116

Short Answer

SCENARIO 16-13
Given below is the monthly time series data for U.S. retail sales of building materials over a
specific year. $$\begin{array} { | c | c | } \hline \text { Month } & \text { Retail Sales } \\\hline 1 & 6,594 \\\hline 2 & 6,610 \\\hline 3 & 8,174 \\\hline 4 & 9,513 \\\hline 5 & 10,595 \\\hline 6 & 10,415 \\\hline 7 & 9,949 \\\hline 8 & 9,810 \\\hline 9 & 9,637 \\\hline 10 & 9,732 \\\hline 11 & 9,214 \\\hline 12 & 9,201 \\\hline\end{array}$$ The results of the linear trend, quadratic trend, exponential trend, first-order autoregressive,
second-order autoregressive and third-order autoregressive model are presented below in which
the coded month for the 1st month is 0: $\text { Linear trend model: }$
$\begin{array}{lrrrr} & \text { Coefficients } & \text { Standard Error } & \text { t Stat } & \text { P-value } \\\hline \text { Intercept } & 7950.7564 & 617.6342 & 12.8729 & 0.0000 \\\text { Coded Month } & 212.6503 & 95.1145 & 2.2357 & 0.0494\end{array}$

$\text { Quadratic trend model: }$


$\text { Exponential trend model: }$
$\begin{array}{lrrrr}\hline & \text { Coefficients } & \text { Standard Error } & \text { t Stat } & \text { P-value } \\\hline \text { Intercept } & 3.8912 & 0.0315 & 123.3674 & 0.0000 \\\text { Coded Month } & 0.0116 & 0.0049 & 2.3957 & 0.0376\end{array}$


$\text { First-order autoregressive: }$
$\begin{array}{lrrrr} & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & {\text { P-value }} \\\hline \text { Intercept } & 3132.0951 & 1287.2899 & 2.4331 & 0.0378 \\\text { YLag1 } & 0.6823 & 0.1398 & 4.8812 & 0.0009 \\\hline\end{array}$


-Referring to Scenario 16-13, what is the exponentially smoothed forecast for the $13 ^ { \text {th } }$ month
using a smoothing coefficient of W = 0.5 if the exponentially smooth value for the $10 ^ { \text {th } }$ and $11 ^ { \text {th } }$ month are 9,746.3672 and 9,480.1836, respectively?

Distinguish between different AI approaches such as machine learning, neural networks, and natural language processing.

Understand how AI can analyze massive datasets to recognize patterns and make recommendations (data mining).

Recognize how technology enables creativity and the sharing of information (cognitive surplus).

Identify methods and tools for enhancing reality and human experience through technology (augmented reality, affective computing).

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Definitions:

Direct Write-off Method

An accounting method where uncollectible accounts receivable are directly written off against income at the time they are deemed uncollectible.

Uncollectible Receivables

Amounts owed to a company that it does not expect to collect and thus considers a loss.

Journalize

The process of recording transactions in an accounting journal, noting the debit and credit aspects of each transaction.

Percent of Sales Method

A financial analysis technique used to forecast future expenses or account balances as a percentage of sales revenue.