Housing Costs at the Turn of the Century   The following table shows the average price of a two-bedroom apartment in a downtown area from 1994 to 2004
(t = 0
represents 1994).
Year t	0	2	4	6	8	10
Price p
($ million)	0.58	0.60	0.80	1.15	1.40	1.80
(a)
Use technology to obtain the linear regression line and correlation coefficient r, with all coefficients rounded to two decimal places.

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If you have any questions or need further details on this topic, feel free to ask! Here are some follow-up questions you might find useful:

1. How do we interpret the slope of a regression line in this context?
2. What does the correlation coefficient tell us about the relationship between time and housing prices?
3. What would a negative correlation coefficient mean for this data?
4. How could we use this regression line to predict future housing prices?
5. How does rounding the coefficients affect the accuracy of predictions?

**Tip:** Linear regression assumes a straight-line relationship between the variables, so if your data shows curvature, a different model might be more appropriate.

Housing Costs at the Turn of the Century: The following table shows the average price of a two-bedroom apartment in a downtown area from 1994 to 2004 (t = 0 represents 1994). Year t 0 2 4 6 8 10, Price p ($ million) 0.58 0.60 0.80 1.15 1.40 1.80. (a) Use technology to obtain the linear regression line and correlation coefficient r, with all coefficients rounded to two decimal places.

This problem focuses on using linear regression to model housing costs between 1994 and 2004. It includes calculating the regression line and correlation coefficient based on provided data. Ideal for students in Grades 10-12.

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