Whether the statement “in least square regression, the response variable is normally distributed with mean μ y / x and standard deviation σ .

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Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 12.3, Problem 2AYU

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Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

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Answer 2

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Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 12.3, Problem 2AYU

To determine

Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

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Answer 3

Question

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 12.3, Problem 2AYU

To determine

Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

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Answer 4

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Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 12.3, Problem 2AYU

To determine

Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

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Answer 5

Chapter 12.3, Problem 2AYU

To determine

Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

Answer 6

Chapter 12.3, Problem 2AYU

To determine

Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

Answer 7

Chapter 12.3, Problem 2AYU

To determine

Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

Answer 8

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Answer 11

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Whether the statement “in least square regression, the response variable is normally distributed with mean μ y / x and standard deviation σ .

Solution Summary: The author explains that the distribution of the response variable is normal in least squares regression. The mean value of responses in the population linearly depends on the explanatory variable x.

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Whether the statement “in least square regression, the response variable is normally distributed with mean μy/x and standard deviation σ .

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