The analysis of how sales prices relate to the number of bedrooms is most effectively done through which method?

The analysis of how sales prices relate to the number of bedrooms is most effectively performed using regression analysis. This method allows for a deeper examination of the relationship between a dependent variable (in this case, sales prices) and one or more independent variables (like the number of bedrooms).

Regression analysis helps to quantify the effect of each additional bedroom on the price of a property, providing not only insights into the correlation but also information on the strength and nature of that relationship. It can reveal how sales prices change with variations in the number of bedrooms, allowing for more accurate predictions and assessments.

While cross-tabulation presents a way to observe relationships between categorical variables, it does not allow for the same depth of analysis or prediction that regression provides. Scatter plots can illustrate relationships between two quantitative variables visually, but they lack the ability to account for the influence of multiple factors simultaneously as regression does. Time series analysis is focused on observing changes over time rather than the correlation between variables at a single point in time, which makes it unsuitable in this context for assessing the impact of bedroom count on sales prices.