Please I need a lot of help with the questions below can someone explain this in the form the questions are please not something else I am very confused; all the needed examples are on the bottom but I need more help.

Data collection

Sampling the data:Select a random sample of 50 houses.Describe how you obtained your sample data (provide Excel formulas as appropriate).]

[Sampling the data:Identify yourpredictor and response variables.]

[Scatterplot:Create and insert a correctly labeled scatterplot of your predictor and response variables to ensure they are appropriate for developing a linear model.]

Data Analysis

[Histogram:Create andinsert a histogram for the first variable. Be sure to include appropriate labels.]

[Histogram:Create andinsert a histogram for the second variable. Be sure to include appropriate labels.]

[Summary statistics:Create andinsert a table to show the summary statistics (mean, median, standard deviation) for both variables.]

[Interpret the graphs and statistics:Interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for house sales and square footage.]

[Interpret the graphs and statistics:Compare and contrast center, spread, shape, and any unusual characteristic for your sample of house sales with the national population. Also, determine whether your sample is representative of the national housing market sales. Note:In the learning management system, under Supporting Materials, seeNational Summary Statistics and Graphs Real Estate Data PDF.]

Develop Regression Model

[Scatterplot:Create and insert the scatterplot of the variables with a line of best fit and the regression equation. [Based on your scatterplot, explain whether a regression model is appropriate.]

[Discuss associations:Discuss the associations in the scatterplot, including the direction, strength, and form, in the context of your model.]

[Discuss associations:Identify any possible outliers or influential points and discuss their effect on correlation.]

[Discuss associations:Discuss keeping or removing outlier data points and what impact your decision would have on your model.]

[Calculate r:Calculate the correlation coefficient and explain how the calculated r value supports what was noticed in your scatterplot.]

Determine the Line of Best Fit

[Regression equation:Write the regression equation (i.e., line of best fit) and clearly define your variables.]

[Interpret regression equation:Interpret the slope and intercept in context. For example, answer the questions: What does the slope represent in this situation? What does the intercept represent? Revisit the Scenario section in the learning management system.]

[Strength of the equation:Provide and interpretR-squared. Determine the strength of the linear regression equation you developed.]

[Use regression equation to make predictions:Use the regression equation to predict how much you should list your home for based on the assumed square footage of your home at 1500 square feet.]