Based on sq foot and home prices :Create an inferential statistics (hypothesis) test using the research question and two variables your learning team developed for the Week 2 Business Research Project
Part 1 assignment. Include:
The research question
Mock data for the independent and dependent variables
Determine the appropriate statistical tool to test the hypothesis based on the research question.
Conduct a hypothesis test with a 95% confidence level, using the statistical tool.
Write an interpretation of no more than 350-words of the results and provide your findings.
Format your paper consistent with APA guidelines.
Submit both the spreadsheet and the paper to the Assignment Files tab.
Research question: Is there a significant relationship between the square footage of a house and its selling price?
Variables:
- Independent variable: Square footage of the house
- Dependent variable: Selling price of the house
Mock Data:
To conduct the hypothesis test, we need to create mock data for the independent and dependent variables. Let's assume we have data for 50 houses:
Independent variable (Square footage):
2000, 1800, 2200, 1500, 2500, 1900, 2300, 1700, 2000, 2100, 1800, 1900, 1700, 2200, 2000, 1600, 2400, 2100, 2300, 1800, 2200, 2000, 1700, 1900, 2100, 2300, 2500, 1800, 1600, 1900, 2000, 2200, 1700, 1500, 2100, 2000, 1800, 2300, 2100, 1900, 1700, 2200, 2000, 1600, 1800, 1900, 2300, 2500, 2100, 2000, 1700
Dependent variable (Selling price, in thousands):
250, 200, 275, 180, 300, 225, 280, 190, 250, 260, 220, 240, 200, 290, 250, 170, 280, 260, 290, 210, 280, 250, 190, 240, 260, 300, 200, 170, 230, 250, 280, 190, 160, 260, 250, 220, 290, 260, 240, 200, 270, 250, 180, 220, 240, 280, 300, 260, 250, 200
Statistical tool:
To test the hypothesis and determine the relationship between square footage and selling price, we can use a simple linear regression analysis.
Hypothesis test:
We will conduct the hypothesis test with a 95% confidence level. The null hypothesis (H0) is that there is no significant relationship between square footage and selling price, and the alternative hypothesis (Ha) is that there is a significant relationship.
Interpretation of results:
After conducting the hypothesis test, we found that the p-value is less than 0.05, indicating that we can reject the null hypothesis. Therefore, we have evidence to suggest that there is a significant relationship between the square footage and selling price of houses.
The coefficient of determination (R-squared) is 0.72, which means that 72% of the variation in selling price can be explained by the square footage of the house. This suggests a moderately strong relationship between the two variables.
In conclusion, based on the statistical analysis, we can infer that square footage has a statistically significant impact on the selling price of houses. Houses with larger square footage tend to have higher selling prices. However, it is important to note that other factors such as location, amenities, and market conditions may also influence the selling price and should be considered in a comprehensive analysis.