Examlex

Solved

Consider the Following Set of Quarterly Sales Data, Given in Thousands

question 17

Short Answer

Consider the following set of quarterly sales data, given in thousands of dollars.
Consider the following set of quarterly sales data, given in thousands of dollars.    The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y(t) = β<sub>0</sub> + β<sub>1</sub><sub>t</sub> + β<sub>Q1</sub>(Q1) + β<sub>Q2</sub>(Q2) + β<sub>Q3</sub>(Q3) + E<sub>t</sub>. In this model, there are three binary seasonal variables (Q1, Q2, and Q3), where Qi is a binary (0,1) variable defined as: Qi = 1, if the time series data is associated with quarter i; Qi = 0, if the time series data is not associated with quarter i. The results associated with this data and model are given in the following Minitab computer output. The regression equation is Sales = 2442 + 6.2 Time − 693 Q1 − 1499 Q2 + 153 Q3      Analysis of Variance    At α = .05, test the significance of the model. The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y(t) = β0 + β1t + βQ1(Q1) + βQ2(Q2) + βQ3(Q3) + Et. In this model, there are three binary seasonal variables (Q1, Q2, and Q3), where Qi is a binary (0,1) variable defined as:
Qi = 1, if the time series data is associated with quarter i;
Qi = 0, if the time series data is not associated with quarter i.
The results associated with this data and model are given in the following Minitab computer output.
The regression equation is
Sales = 2442 + 6.2 Time − 693 Q1 − 1499 Q2 + 153 Q3
Consider the following set of quarterly sales data, given in thousands of dollars.    The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y(t) = β<sub>0</sub> + β<sub>1</sub><sub>t</sub> + β<sub>Q1</sub>(Q1) + β<sub>Q2</sub>(Q2) + β<sub>Q3</sub>(Q3) + E<sub>t</sub>. In this model, there are three binary seasonal variables (Q1, Q2, and Q3), where Qi is a binary (0,1) variable defined as: Qi = 1, if the time series data is associated with quarter i; Qi = 0, if the time series data is not associated with quarter i. The results associated with this data and model are given in the following Minitab computer output. The regression equation is Sales = 2442 + 6.2 Time − 693 Q1 − 1499 Q2 + 153 Q3      Analysis of Variance    At α = .05, test the significance of the model. Consider the following set of quarterly sales data, given in thousands of dollars.    The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y(t) = β<sub>0</sub> + β<sub>1</sub><sub>t</sub> + β<sub>Q1</sub>(Q1) + β<sub>Q2</sub>(Q2) + β<sub>Q3</sub>(Q3) + E<sub>t</sub>. In this model, there are three binary seasonal variables (Q1, Q2, and Q3), where Qi is a binary (0,1) variable defined as: Qi = 1, if the time series data is associated with quarter i; Qi = 0, if the time series data is not associated with quarter i. The results associated with this data and model are given in the following Minitab computer output. The regression equation is Sales = 2442 + 6.2 Time − 693 Q1 − 1499 Q2 + 153 Q3      Analysis of Variance    At α = .05, test the significance of the model. Analysis of Variance
Consider the following set of quarterly sales data, given in thousands of dollars.    The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y(t) = β<sub>0</sub> + β<sub>1</sub><sub>t</sub> + β<sub>Q1</sub>(Q1) + β<sub>Q2</sub>(Q2) + β<sub>Q3</sub>(Q3) + E<sub>t</sub>. In this model, there are three binary seasonal variables (Q1, Q2, and Q3), where Qi is a binary (0,1) variable defined as: Qi = 1, if the time series data is associated with quarter i; Qi = 0, if the time series data is not associated with quarter i. The results associated with this data and model are given in the following Minitab computer output. The regression equation is Sales = 2442 + 6.2 Time − 693 Q1 − 1499 Q2 + 153 Q3      Analysis of Variance    At α = .05, test the significance of the model. At α = .05, test the significance of the model.


Definitions:

Aggressor

A person or entity that initiates hostility or attack, whether physical or psychological, against others.

Dominator

An entity or individual that exercises control or exert supremacy over others in a commanding or dominating manner.

Modeled Behavior

Actions displayed by an individual that serve as a reference for others, potentially influencing their behavior through observation and imitation.

Using Praise

The act of expressing approval or admiration to encourage or reinforce positive behavior or achievements.

Related Questions