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Five Most Common Statistical Projects - Essay Example

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This essay "Five Most Common Statistical Projects" focuses on the appearance of cell phones after twenty seconds in the mold is equal to appearance after ten seconds. The appearance of cell phones after twenty seconds in the mold is better than appearance after ten seconds…
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Five Most Common Statistical Projects
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Conclusion: The number of particles after method 2 is higher than after method 1. 6-27The molecular weight effect is plotted as follows: The data follows a normal probability plot that is skewed to the left. The effect seems to be skewed to the left meaning that the molecular weight effect is centered between 2400 and 2600.Analysis of Variance: The following table describes the analysis of variance of the molecular weight effect. It is noted that the mean is 2499 and the standard deviation is 126 which indicates the little variance of the molecular weight effect.

Curvature is skewed to the left according to the skewness statistic. Regression Analysis: Regression analysis is conducted to predict molecular weight from other factors.First Run: Based on p-value and significance of results. D and B are excluded. Regression Second Run: It is suggested to remove the viscosity variable due to its insignificance. Regression Third Run:Model and equation to predict molecular weight:Molecular weight = 2499.5 + 100.6 (C) + 61.9 (A) The model is adequate as it predicts 70% of molecular weight from A and C.

Viscosity is plotted on a histogram graph as follows: The histogram of viscosity does not show that the variable is normally distributed. Analysis of Variance: The following table describes the analysis of variance of the viscosity effect. It is noted that the mean is 1499 and the standard deviation is 67 which indicates the little variance of the molecular weight effect. Curvature is skewed to the left according to the skewness statistic. Regression to predict Viscosity: Based on the p-value, it is determined to omit the variable's molecular weight.

Regression Second Run: Based on p-value, it is determined to. The following table describes the analysis of variance of the molecular weight effect. It is noted that the mean is 2499 and the standard deviation is 126 which indicates the little variance of the molecular weight effect. Curvature is skewed to the left according to the skewness statistic. The following table describes the analysis of variance of the viscosity effect. It is noted that the mean is 1499 and the standard deviation is 67 which indicates the little variance of the molecular weight effect.

Curvature is skewed to the left according to the skewness statistic. From the regression equation: it is determined that to decrease viscosity it is best to increase catalyst concentration. From coefficients of variance, it is suggested to decrease time and pressure and increase temperature and molecular weight.

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