Math/Physic/Economic/Statistic Problems
When using linear regression, what would you expect the scatterplot to look like? Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.
Interpret the graphs and statistics: Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables. Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales?
Explain if a regression model is appropriate to develop based on your scatterplot.
Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model. Identify any possible outliers or influential points and discuss their effect on the correlation.
Discuss keeping or removing outlier data points and what impact your decision would have on your model. Find r: Find the correlation coefficient (r).
Explain how the r value you calculated supports what you noticed in your scatterplot.
Did you see the results you expected, or was anything different from your expectations or experiences? What changes could support different results, or help to solve a different problem? Provide at least one question that would be interesting for follow-up research.
