• You must include the following the sections in your project.Introduction (10 points):
• Include a title.
• Introduce your topic.
• Motivate your study.
• State your research question.
• State where you obtained your data.
• State what statistical package and version you are using to analysis the data (it should be R).
• Exploratory data analysis (10 points):
• Give the variables, what they measure (if it's not clear from the variable name), which is the explanatory variable and which are the response variables, and whether each is categorical or numerical.
• Make a scatterplot matrix, and comment on any outliers.
• If you have a qualitative/categorical variable, include a boxplot of the response versus
• the levels of the categorical variable.
• 1

Regression model building (10 points):

First fit a model with each of the predictors "as is".

Check the four regression model assumptions, and include graphs.Add interactions and/or transformations as needed.

Simplify the model, using hypothesis test(s).

Results (10 points):

• Give the estimated regression equation of the final model.
• Check that the final model results in residuals that appear to satisfy the four regression
• model assumptions.
• Comment on any outliers or other influential points, or state that there are none.
• Check for multicollinearity if you have two or more numerical/quantitative predictors.
• Comment on the R-squared and the regression standard error, interpreting both of them.
• Effects of each predictor on the response and intervals (10 points):
• Find the predictor effect(s) on the response.
• Include a graph of the predictor effect(s).
• Findaconfidenceintervalandapredictionintervalataparticularvalueofthepredictors (you pick the values).
• Conclusion and Future Work (10 points):
• Conclude the paper.
• Suggest future work and/or ask some future questions.

The research is about The Anscombe data frame which has 51 rows and 4 columns.