A paper package for gauze surgical sponges is created by feeding two rolls of paper into a machine to form the top and bottom of the package. The top roll comes pretreated with adhesive applied in a chevron pattern. The seal is created when a heated platen is applied to the package for a certain length of time. Seal strength, measured in pounds per inch, is the primary response of interest.

An engineer wants to predict seal strength, given the machine settings of platen temperature, application pressure, and dwell time. In addition other factors may affect the strength of the seal. For example, she suspects that the relative humidity in the plant affects the adhesion. One hundred observations taken from production records from the previous five months are in the accompanying data file.

The data involves Platen temperature (F)X₁, Application pressure (psi) X₂, Dwell time (s) X₃, Relative humidity (%) X₄, and Seal strength (psi) Y.

need report analyzing all of the factors, graphically, determining which distribution best fits each factor, performing hypothesis testing and a few factors, calculating confidence intervals for factors, and developing a multiple linear regression model to predict seal strength.

Your project should be split into the following sections:

Introduction and Graphical analysis

Determine a method to graphically display each factor on its own graph.

Identify and graphically show the distribution that best fits each factor and seal strength among Normal, Weibull, Gamma, and Lognormal.

Confidence Intervals and Hypothesis Testing

Calculate 95% confidence intervals for each factors, and also seal strength.

It has long been assumed that the application pressure is critical to the seal strength. The application pressure should be 1.5 psi. With a historical standard deviation of 0.26, can manufacturer safely say the application pressure is truly 1.5 psi. Perform a statistical analysis to test this. Share all relevant numerical data.

In addition to this, the Platen temperature should be greater than 280F. With a known historical standard deviation of 55F , can the manufacturer say they are meeting this standard? Perform a statistical analysis to test this. Share all relevant numerical data.

Regression Analysis and Conclusion

Develop a multiple linear regression model to predict seal strength based on the other four factors and assess the model for significance and variance explanation. Then, evaluate the significance of each of the factors. Are all factors significant? Why or why not? If all factors are not significant, develop a model with only significant factors.

All need to be solved using minitab only