SNHU MAT 240 MODULE 4 PROJECT 1 LATEST 2024 WITH COMPLETE SOLUTION.

SNHU MAT 240 MODULE 4 PROJECT 1 LATEST 2024 WITH COMPLETE SOLUTION. Introduction Building a model to forecast 2019 home sales prices is the primary objective of this project. This will be achieved by establishing a research subject, performing an in-depth statistical analysis, and presenting the study results. For this inquiry, a linear regression model is the most suitable option since the listing price of a property is closely correlated with its square footage. Therefore, we can expect a direct relationship between the listing price and the square footage, which a linear pattern in the scatterplot will represent. In this study, the listing price of a property is determined by the size of the home. Given this, the house and the property's square footage are considered independent variables, while the listing price is considered the dependent variable. Data Collection In order to determine the appropriate size of the sample for the inquiry, a total of fifty houses were selected at random. To create random numbers, the = rand() function in Microsoft Excel was used. These values were then organized and assigned to the appropriate categories (SNHU A11y Remediated Videos, 2021). In order to get the sample, a random selection of fifty rows was done. The listing price would be the dependent variable, whereas the square footage would be the independent variable in this scenario.