a) If the correlation between height and weight is .70, when we use height to predict weight: we can account for 70% of the variance in weight we can account for 14% of the variance in weight we can account for 49% of the variance in weight we can account for 83% of the variance in weight B) An organisation that you work for has asked a statistician to help them predict yearly profit (in millions AUD) from annual turnover rate (operationalised as the number of employees who left the organisation that year). The statistician provides them with the following regression equation: Ŷ = 5.67 – 0.13X. The organisation asks you to interpret this equation for them. Which of the following interpretations is correct? For each person who leaves the organisation, there is a 0.13 million AUD increase in profit The predicted yearly profit when there is no turnover is 5.67 million AUD The average amount of error associated with this regression equation is 0.13 For each person who leaves the organisation, there is a 5.67 million AUD decrease in profit
a) If the
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we can account for 70% of the variance in weight |
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we can account for 14% of the variance in weight |
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we can account for 49% of the variance in weight |
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we can account for 83% of the variance in weight |
B)
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An organisation that you work for has asked a statistician to help them predict yearly profit (in millions AUD) from annual turnover rate (operationalised as the number of employees who left the organisation that year). The statistician provides them with the following regression equation: Ŷ = 5.67 – 0.13X. The organisation asks you to interpret this equation for them. Which of the following interpretations is correct?
For each person who leaves the organisation, there is a 0.13 million AUD increase in profit
The predicted yearly profit when there is no turnover is 5.67 million AUD
The average amount of error associated with this regression equation is 0.13
For each person who leaves the organisation, there is a 5.67 million AUD decrease in profit
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