WorksheetsPractical 9 Task 3
Total questions: 10
Worksheet time: 27mins
Use Minitab to create a scatterplot for the data. What is the relationship between price and distance?
Negative
Positive
No relationship
Identify the variables used in this study.
Explanatory variable: Distance
Response variable: Price
Explanatory variable: Price
Response variable: Distance
Using Minitab, what is the linear regression model between price and distance?
Conduct a test with the following hypotheses H0: β = 0 vs H1: β ≠ 0 to see if there is a linear relationship between price and distance. Assume α = 0.05.
As P-value ≈ 0 < α = 0.05, H0 is rejected. β is significantly different from 0. There is a significant linear relationship between distance and price.
As P-value ≈ 0 < α = 0.05, H0 is not rejected. β is not significantly different from 0. There is no significant linear relationship between distance and price.
As P-value = 0.882 > α = 0.05, H0 is not rejected. β is not significantly different from 0. There is no significant linear relationship between distance and price.
As P-value = 0.882 > α = 0.05, H0 is not rejected. ρ is not significantly different from 0. There is no significant linear relationship between distance and price.
What is the y-intercept? Give your answer correct to 1 decimal place.
(a)
What is the slope of the regression line? Give your answer correct to 2 d.p.
(a)
Interpret the slope of the regression line.
For every 1 km increase in distance, price of flat decrease by $22970 on average.
For every 1 km increase in distance, price of flat increase by $22970 on average.
For every $1000 increase in price of flat, distance decrease by 30.9m on average.
For every $1000 increase in price of flat, distance increase by 30.9m on average.
Predict the price for a flat that is 5 km from the train station.
$145,750
$126,935
Not applicable, as distance of 5 km is out of range of the data used to fit the model (extrapolation).
What is the R2? Give your answer correct to 1 d.p.
(a)
Which is/are correct interpretation(s) for the R2 obtained?
71% of the variation in price can be explained by the fitted model.
71% of the variation in price can be explained by the linear relationship between price and distance.
71% of the value of price is due to distance.
71% of the variation in distance can be explained by price.
