To investigate the relationship between the selling price of a house, yy, in dollars, and the size of the house xx, in square feet, a local builder collected data on a random sample of 120 houses from a certain region. Assume that the conditions for inference for the slope of a regression line are met. The resulting 95 percent confidence interval for the population slope of the regression line relating price and size is given by (62,99). The local builder claims that the selling price of houses from the region increases by $104 for every extra square foot of space in the house. Which of the following best describes the conclusion that can be reached about this claim based on the confidence interval? A)The claim is supported by the interval, since the interval does not contain the value 0. B)The claim is supported by the interval, since all values in the interval are positive. C)The claim is supported by the interval, since the interval does not contain the value 104. D)The claim is not supported by the interval, since the interval does not contain the value 0. E)The claim is not supported by the interval, since the interval does not contain the value 104.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
To investigate the relationship between the selling price of a house, yy, in dollars, and the size of the house xx, in square feet, a local builder collected data on a random sample of 120 houses from a certain region. Assume that the conditions for inference for the slope of a regression line are met. The resulting 95 percent confidence interval for the population slope of the regression line relating price and size is given by (62,99).
The local builder claims that the selling price of houses from the region increases by $104 for every extra square foot of space in the house. Which of the following best describes the conclusion that can be reached about this claim based on the confidence interval?
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A)The claim is supported by the interval, since the interval does not contain the value 0.
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B)The claim is supported by the interval, since all values in the interval are positive.
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C)The claim is supported by the interval, since the interval does not contain the value 104.
D)The claim is not supported by the interval, since the interval does not contain the value 0. -
E)The claim is not supported by the interval, since the interval does not contain the value 104.
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