1. The relationship between cost and home sales
Debbie Lemon and Dan Mollette
Algebra I

2. Our Predictions
Since many of the homes in our neighborhood are smaller and older homes, we predicted that homes would not sell for more than $400, We also reviewed the MLS listings online.

3. WE EXPLORED THE RELATIONSHIP BETWEEN THE COST OF HOMES IN OUR AREA AND THE NUMBER OF HOMES SOLD.
Data was found online at:

4. Confirming the Linear Data
We plotted the points using x as the price of houses sold and y as the number of houses sold.
The scatterplot of the data indicated a strong negative correlation. This relationship was negative because as the cost of the houses increased, the number of houses sold decreased.
The line of best fit was drawn and using two points on the line, we calculated the slope.

5. Writing the Equation
Once we found the slope, we easily found the y intercept by substituting into the slope- intercept formula and looking on the graph.
y = -.88x

6. Calculating the equation
We used the TI-83 to enter the data, graph the relationship and determine the line of best fit.
y = -.79x

7. Conclusions
1. Our data was linear because the number of homes sold decreased at a similar rate of change compared to the number of homes sold.
2. The slope is negative because as the y values (cost of homes) increase, the x values (number of homes sold) decreases.
3. The equation we created using the calculations of the points we chose on the line of best fit (y = -.88x ) and the calculator equation (y = -.79x ) were closely related since they looked almost the same when graphed.

8. Conclusions
According to our graphs and our equations, we can predict that there will be no homes sold in this neighborhood when the cost of the home reaches approximately $303,
Our prediction was much higher since many of the homes described on the website were listed at higher prices.