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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.


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Diagnostic classification refers to the systematic categorization of mental and physical health conditions based on standardized criteria and symptoms.

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A wide range of conditions that affect mood, thinking, behavior, and functioning, often diagnosed according to standardized criteria.

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Lacking in resources, wealth, or the essentials of life, often leading to limited opportunities and well-being.

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