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# Linear Regression Model watch

1. As part of a question sheet, I have been using a set of data and been analysing it to see if it would fit the linear regression model. As part of this I have been doing hypothesis testing and confidence and prediction ontervals. Last question says:

"A businessman is considering buying into a company outside your data sample with a RSRatio of 0.05. What is the probability that their PERatio is above 8?" where RSRatio is our explanatory variable and PERatio is our response.

If anyone could provide any guidance or help with this question would be very appreciated!
2. (Original post by mollyjordansmith)
As part of a question sheet, I have been using a set of data and been analysing it to see if it would fit the linear regression model. As part of this I have been doing hypothesis testing and confidence and prediction ontervals. Last question says:

"A businessman is considering buying into a company outside your data sample with a RSRatio of 0.05. What is the probability that their PERatio is above 8?" where RSRatio is our explanatory variable and PERatio is our response.

If anyone could provide any guidance or help with this question would be very appreciated!
In linear regression, the response variable is modelled as a normal random variable with mean given by the linear predictor (built out of your explanatory variables) and standard deviation given by the residuals (which you usually read off from software). That’s enough information to calculate the required probability.

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Updated: February 7, 2018
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