# STAT 219 Linear Regression Project Part II Statistical Analysis Due Day 5 of Week 4 1. Run… 1 answer below »

STAT 219 Linear Regression Project

Part II Statistical Analysis Due Day 5 of Week 4

1. Run relevant descriptive statistics and graphs using Minitab. (no more than 30% of the paper) Createahistogramforeach ofthequantitative variables. Createaboxplot foreach ofthe quantitative variables. Calculate thedescriptive statisticstostudy thecenter(MeanandMedian),dispersion (StandardDeviationandRange),distribution (Skewand Kurtosis),andposition(re: outliers-if anyand bywhatcriteria)for each ofthe quantitative variables.Describewhat thesevalues tell you abouteach ofthevariables.(Note:The statisticsmentionedin parenthesis mustbeaddressed; however,you maywish toinclude additional statistics if they helpto better“paintthe picture” ofyour dataset.) Decidenotonly whether thedataaresymmetricor skewed,butwhetherthedataare sufficiently symmetric to maketheassumptionofnormality.Give yourreasoningaswell as statingyour decision aboutthe shapeof thedata.

2. Create and analyzeascatterplot.

· Use Minitab to create a scatter plot with the regression line.

· Use the scatter plot to decide if there is a significant linear relationship between the variables.

· Categorize the correlation as strong/weak/insignificant.

· If a strong or weak correlation exists categorize it as positive or negative.

· Analyze points in the scatter plot that appear not to follow the trend of the regression line. Try to discern why these points do not follow the trend and whether the points should be kept in the analysis.

3. Analyze numeric measures of correlation

· Find thecorrelation coefficient, r and explain its relevance.

· Explain the relevance and practical meaning of R-squared.

· Examinewhetherevidenceofa relationship betweentwovariables exists using the p-value.

· Explain the relevance of the slope of the regression line.

4. Predictions

· Find the linearregressionequation.

· Elaborate on the reliability of predictions. Should the equation be used for predictive purposes?

· If appropriate, select a few values of the predictor variable and make the prediction using the regression equation. If not, explain what approach you would take to make predictions.

Submission Requirements

1. Briefly, write up and submit your conclusions and reasoning.
2. Copy/paste any output and/or graphs/charts referenced in your write up into the document containing your brief conclusions and reasoning.
3. Submit your Minitab file.