### Interpretation of coefficient of determination

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Interpretation of coefficient of determination

If computing a causal linear regression model of y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that:

1. y = a + bX is a good forecasting method.

2. Y = a + bX is not a good forecasting method.

3. a multiple linear regression model is a good forecasting method for the data.

4. a multiple linear regression model is not a good forecasting method for the data.

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 Regression line and making predictions : Finding the Equation of the Regression Line and Making Predictions. Find the regression equation, Strategy of sherman anti-trust act : The strategy of the Sherman Anti-Trust Act and other U.S. antimonopoly legislation is to ensure that each company has meaningful competitors in every product market in which it participates. Regression equation and coefficient of determination : Which of these following statements provides the best guidance for the model building? Select one of the strategies listed below : elect one of the strategies listed below that are widely used for entering foreign markets and discuss in detail the proposed strategy. Interpretation of coefficient of determination : If computing a causal linear regression model of y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that: Target market in the united states : Describe the target market in the United States, including customer demographics and income levels. Describe the competition the product would face in the United States and how you would create a competitive advantage. Name at least two competitors.. Testing of regression coefficient : Is there evidence that teams with higher total payrolls tend to be more successful? Justify your answer. Propose example for some industry : Write down an example for some industry of your choice such as coffee, Movie Theatre, pizza, credit card, trash/waste removal, utility or automotive service. Deriving the regression equation : Deriving the regression equation, testing the model fit and obtains confidence interval for estimated values.

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