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• $H_0:{\beta }_1=0;H_A:{\beta }_1\ne 0$

• $H_0:{\beta }_1=0;H_A:{\beta }_1>0$

• $H_0:{\beta }_1<0;H_A:{\beta }_1>0$

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• The data provide convincing evidence that wives’ and husbands’ heights are positively correlated. The p-value, as reported in the table, is smaller than 0.05, so we reject $H_0$.

• The data does not provide convincing evidence that wives’ and husbands’ heights are positively correlated. The p-value, as reported in the table, is significant, so we fail to reject $H_0$.

• There is no sufficient information to make a conclusion.

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• Slope: For each additional inch in husband’s height, the average wife’s height is expected to be an additional (slope value) inches on average.

• Slope: For each additional inch in wife’s height, the average husbands’s height is expected to be an additional (slope value) inches on average.

• Intercept: Men who are 0 inches tall are expected to have wives who are on average, (intercept value) inches tall.

• Intercept: Men who are (intercept value) inches tall are expected to have wives who are on average, 0 inches tall.

• The intercept here is meaningless, and it serves only to adjust the height of the line.

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Please enter a numeric value in.

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Please enter a numeric value in.

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• The prediction based on this regression model is very reliable from the given R value.

• Since $R^2$ is low, the prediction based on this regression model is not very reliable.

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• Yes

• No