Question

In: Statistics and Probability

A 2 ^3 full factorial screening experimental design was performed to identify the important factors affecting...

A 2 ^3 full factorial screening experimental design was performed to identify the important factors affecting the percent conversion in a chemical process. Two factors, temperature in C (x1) and reactant concentration (x2) were identified as the key process input variables and the method of steepest ascent was applied to identify the maximum percent conversion area. Create and analyze a central composite design using the data in the following table (in standard run order). Test the residuals assumption and comment on the adequacy of the model. Identify the temperature and reactant concentration setting that maximizes percent conversion.

Std. Run Temp Reactant % Conversion
1 200 15 53
2 250 15 88
3 200 25 79
4 250 25 83
5 189.65 20 58
6 260.35 20 88
7 225 12.93 75
8 225 27.07 84
9 225 20 86
10 225 20 89
11 225 20 83
12 225 20 81

Solutions

Expert Solution

Sol:

Regression Equation can be calculated from anova table and Correlation Coeficient table which is calculated through Excel functions:

ANOVA
df SS MS F Significance F
Regression 2 970.9791 485.4895 8.183364 0.009438
Residual 9 533.9376 59.3264
Total 11 1504.917
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -29.5602 26.9144 -1.0983 0.300584 -90.4448 31.3244 -90.4448 31.3244
X Variable 1 0.407161 0.108936 3.737618 0.004643 0.160731 0.653592 0.160731 0.653592
X Variable 2 0.843277 0.54468 1.548206 0.15598 -0.38888 2.07543 -0.38888 2.07543

Regression Equation can be written as:

Conversion = 29.5 +0.40 Temp +0.8432 Reactant

For maximum prediction there are two sets these are (260.35,20) and (250,25)

Residuals can be calculated as follows:

Std. Run Temp Reactant% Conversion Prediction Residual
1 200 15 53 64.5078 11.5078
2 250 15 88 84.8628 -3.1372
3 200 25 79 72.9398 -6.0602
4 250 25 83 93.2948 10.2948
5 189.65 20 58 64.51032 6.510315
6 260.35 20 88 93.29229 5.292285
7 225 12.93 75 72.93988 -2.06012
8 225 27.07 84 84.86272 0.862724
9 225 20 86 78.9013 -7.0987
10 225 20 89 78.9013 -10.0987
11 225 20 83 78.9013 -4.0987
12 225 20 81 78.9013 -2.0987

The assumption of regression equation is That the regression residuals must be normal distributed

But here mean = -0.01 and Median = 2

So mean and Median are not equal so we can say that residuals are not Normally Distributed


Related Solutions

A 2^3 full factorial screening experimental design was performed to identify the important factors affecting the...
A 2^3 full factorial screening experimental design was performed to identify the important factors affecting the percent conversion in a chemical process. Two factors, temperature in C (x1) and reactant concentration (x2) were identified as the key process input variables and the method of steepest ascent was applied to identify the maximum percent conversion area. Create and analyze a central composite design using the data in the following table (in standard run order). Test the residuals assumption and comment on...
you have a full factorial design with two levels for three factors. every trial had 2...
you have a full factorial design with two levels for three factors. every trial had 2 runs. the difference in response values for every trial were [2,5,4,3,2,3,4,5]. calculate standard error for the effects. how to do this? I tried lots of times.
Consider a 2^5 factorial design. (a)How many factors and levels are considered in this factorial experiment?...
Consider a 2^5 factorial design. (a)How many factors and levels are considered in this factorial experiment? (b)Show all the 32 treatment combinations using a, b, c, d, and e. (c)Suppose you are not able to complete all 32 experiments in a day but you believe 16 experiments can be done in a day. How many blocks do you need under this situation? (d)Revisiting part (c), which interaction effect would be confounded with the blocks? Using the sign method, assign optimal...
Question 3: Consider a 25 factorial design. (a) How many factors and levels are considered in...
Question 3: Consider a 25 factorial design. (a) How many factors and levels are considered in this factorial experiment? (b) Show all the 32 treatment combinations using a, b, c, d, and e. (c) Suppose you are not able to complete all 32 experiments in a day but you believe 16 experiments can be done in a day. How many blocks do you need under this situation? (d) Revisiting part (c), which interaction effect would be confounded with the blocks?...
Explain the relation between Full Factorial Design and the Profits of an organization.
Explain the relation between Full Factorial Design and the Profits of an organization.
Explain the factors affecting the design of reactor systems.
Explain the factors affecting the design of reactor systems.
2. Good sleep or bad sleep? ~ A study was conducted to identify the factors affecting...
2. Good sleep or bad sleep? ~ A study was conducted to identify the factors affecting quality of sleep for university students. A survey of 290 students of different majors aged 17-29 years old revealed that 67.2% of these students suffered from poor sleep. a. Create a 95% confidence interval for the = the population proportion of university students aged 17-29 years old who suffer from poor sleep. Final answer: ( ______________________ , _____________________ ) b. Determine whether each of...
Identify key factors affecting the health of individuals around the world? and the most important one in your country
  PHC212 Identify key factors affecting the health of individuals around the world? and the most important one in your country ( i need 250 words)  
Identify key factors affecting the health of individuals around the world? and the most important one in your country?
  Q: Identify key factors affecting the health of individuals around the world? and the most important one in your country?  
I'm looking for ideas to preform full factorial (2^2 or 2^3) experiment I want a real-world...
I'm looking for ideas to preform full factorial (2^2 or 2^3) experiment I want a real-world applications please.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT