Question

5. The following is a scatterplot of the selling price in dollars) of a house versus the living space (in square feet). Seng Price 500000 450000 400000 350000 300000 250000 200000 1000 1500 2000 2500 Living Area 3000 3500 Which of the following statements is false? There is a positive linear relationship between selling price and living area. The house that is around 1050 square feet sold for about $305,000. An increase in living area causes an increase in selling price. If we predict the selling price using linear regression, we can use the regression model to make predictions for homes that are between 2000 and 3000 square feet.

Answer 1

Option i) This is true because we can see that the trend of the regression line will have a positive slope which means there will be a positive linear relationship between selling price and living area. This is true.

ii) From observation, we can see that around 1050 on the x-axis corresponds to about $305000 on the y-axis. Hence, this is also true.

iii) This option is also true because a positive linear relationship means that if one variable will increase, the other will increase too.

iv) This option is false since we can make prediction for the selling price for any area and not just 2000 to 3000 sq.ft.

So the last statement is false.

* 95% confidence means that if the poll is repeated several times, we would expect the true proportion to fall in 95% of the resulting confidence intervals.

The last option is correct.

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