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SCENARIO 16-13 Given Below Is the Monthly Time Series Data for U.S.retail

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SCENARIO 16-13
Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.
SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. 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:
Linear trend model:
SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance.
Quadratic trend model:
SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. Third-order autoregressive::
SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance.
Below is the residual plot of the various models:
SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year.    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 1<sup>st</sup> month is 0: Linear trend model:     Quadratic trend model:        Third-order autoregressive::     Below is the residual plot of the various models:     -Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance.
-Referring to Scenario 16-13,you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance.


Definitions:

Common-size Statement

A financial statement in which all line items are expressed as a percentage of a base figure within the statement, facilitating comparison across different periods or companies.

Liability Accounts

Accounts on a company's balance sheet that represent the company's obligations to others, including loans, accounts payable, mortgages, and accrued expenses.

Total Assets

The sum of all assets owned by a company, including cash, inventory, property, and equipment, reflected on the balance sheet.

Use of Cash

The ways in which a company or individual employs their available cash resources, including operating expenses, investments, and financing activities.

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