Final answer:
The example illustrates how to use linear regression to predict house prices from the sizes of the houses, where house size is the independent variable and price is the dependent variable.
Step-by-step explanation:
The question pertains to linear regression, a statistical method used in mathematics and economics to predict the value of a dependent variable based on the value of an independent variable.
When given data about the size of houses on the real estate market, you can use this data to predict their price. Since the size of the house (x) is the independent variable and the price (y).
The relationship is continuous, this is indeed a regression problem. In practice, you would plot the data on a scatter plot, draw a line of best fit, and use it to create a regression equation.
When handling a data collection, such as a sample data set of house prices, it's often too overwhelming to look at all individual prices. Instead, summarizing the data with statistics like the median .
Line graphs are commonly used in economics to present such continuous data for better visual understanding. When conducting a regression analysis.
one typically finds the least-squares regression line or the line of best fit to make rough predictions about new data based on the given data set.