Nobody downloaded yet

Summary

The 95% confidence interval on the difference in means is from -4.32 to -1.97. It is the probability of difference to be within this range. This confidence interval indicates that 95% of the time, the difference in appearance and number of defects of cell phones between cooling-down in the mold for ten or twenty seconds will be within the range of 1.97 to 4.32.…

- Subject: Miscellaneous
- Type: Essay
- Level: Undergraduate
- Pages: 14 (3500 words)
- Downloads: 0
- Author: cpagac

Save Your Time for More Important Things

Let us write or edit the essay on your topic
"5 Problems in Statistics (Design of Experiments)"
with a personal 20% discount.

GRAB THE BEST PAPER5 Problems in Statistics (Design of Experiments)

Download file to see previous pages...
Conclusion:

Number of particles after method 2 is higher than after method 1.

6-27

The 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 standard deviation is 126 which indicates 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 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 standard deviation is 67 which indicates little variance of the molecular weight effect. Curvature is skewed to the left according to the skewness statistic.

Regression to predict Viscosity:

Based on p-value, it is determined to omit the variables 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 standard deviation is 126 which indicates 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 standard deviation is 67 which indicates little variance of the molecular weight effect. Curvature is skewed to the left according to the skewness statistic.

From 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. ...Download file to see next pagesRead More

Number of particles after method 2 is higher than after method 1.

6-27

The 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 standard deviation is 126 which indicates 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 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 standard deviation is 67 which indicates little variance of the molecular weight effect. Curvature is skewed to the left according to the skewness statistic.

Regression to predict Viscosity:

Based on p-value, it is determined to omit the variables 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 standard deviation is 126 which indicates 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 standard deviation is 67 which indicates little variance of the molecular weight effect. Curvature is skewed to the left according to the skewness statistic.

From 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. ...Download file to see next pagesRead More

Comments (0)

Click to create a comment

Let us find you another Essay on topic 5 Problems in Statistics (Design of Experiments) for **FREE!**