Using the data in Experiment 2, investigate how the RHA addition and the admixture addition affect the concrete compressive strength.  a. Do the amount of RHA affect the compressive strength? How so?  b. Does the admixture affect the compressive strength? How so?  c. How does the variation in RHA and admixture addition affect the compressive strength? Which of them has the stronger influence on the compressive strength?  d. Do we have sufficient evidence to identify an optimum % addition that will result to maximum compressive strength? Support your answer or provide recommendations, if not possible to know the optimum % addition.   Take your time in answering. I know it is hard. I tried my best to solve this problem, I just want to double check and make sure that my answer is correct. Thank you so much!

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My questions are indicated below. 

Follow up questions for experiment 2:

Using the data in Experiment 2, investigate how the RHA addition and the admixture addition affect the concrete compressive strength. 

a. Do the amount of RHA affect the compressive strength? How so? 

b. Does the admixture affect the compressive strength? How so? 

c. How does the variation in RHA and admixture addition affect the compressive strength? Which of them has the stronger influence on the compressive strength? 

d. Do we have sufficient evidence to identify an optimum % addition that will result to maximum compressive strength? Support your answer or provide recommendations, if not possible to know the optimum % addition.

 

Take your time in answering. I know it is hard. I tried my best to solve this problem, I just want to double check and make sure that my answer is correct. Thank you so much! 

Subject: Statistics for Engineering
Topic: Regression and Experimental Design Analysis
GENERAL INSTRUCTIONS This Final Project covers the topics discussed from Modules 8 to 10 of the course. Here you will work as a researcher who
will analyze the results of experiments you conducted for your research project. You will apply everything you learned in the modules in analyzing and
interpreting the results of the experiments. Your answers will be manually checked. Unless otherwise stated, round off your numeric answer up to two
decimal places.
This activity consists of two parts. Given the experimental data below, perform the appropriate statistical analyses to answer the research questions. Your
task is to write the Results and Discussion and Conclusion based on the data presented. You may assume parameters (e.g, significance level, confidence
level) that are not explicitly stated but state clearly all your assumptions. Provide a separate narrative for each experiment.
EXPERIMENT 1: In biofiltration of wastewater, air discharged from a treatment facility is passed through a damp porous membrane that causes
contaminants to dissolve in water and be transformed into harmless products. Air discharge usually contains hydrogen sulfide, organic sulfides, and other
volatile organic compounds (VOCS). For this experiment, it is desired to investigate the relationship between air inlet temperature and removal efficiency
of porous membrane. The accompanying data on x = inlet temperature (°C) and y = removal efficiency (%) is shown below.
Removal
Removal
Observation Temp
"Observation Temp
1
7.68
98.09
17
8.55
98.27
2
6.51
98.25
18
7.59
98
3
6.49
97.82
19
6.94
98.09
4
5.48
97.82
20
8.31
98.25
5
6.57
97.82
21
10.5
98.41
6
10.13 97.93
22
16.02 98.51
15.71 98.38
23
17.83
98.71
16.77 98.89
24
17.03 98.79
9.
17.13 98.96
25
16.18 98.87
10
17.63
98.9
26
16.31
98.76
11
16.72 98.68
27
14.44 98.58
12
15.45 98.69
28
12.78
98.73
13
12.21 98.51
29
12.25 98.45
14
11.44 98.09
30
11.64
98.37
15
10.17 98.25
31
11.34 98.36
16
9.64
98.36
32
10.97 98.45
Transcribed Image Text:Subject: Statistics for Engineering Topic: Regression and Experimental Design Analysis GENERAL INSTRUCTIONS This Final Project covers the topics discussed from Modules 8 to 10 of the course. Here you will work as a researcher who will analyze the results of experiments you conducted for your research project. You will apply everything you learned in the modules in analyzing and interpreting the results of the experiments. Your answers will be manually checked. Unless otherwise stated, round off your numeric answer up to two decimal places. This activity consists of two parts. Given the experimental data below, perform the appropriate statistical analyses to answer the research questions. Your task is to write the Results and Discussion and Conclusion based on the data presented. You may assume parameters (e.g, significance level, confidence level) that are not explicitly stated but state clearly all your assumptions. Provide a separate narrative for each experiment. EXPERIMENT 1: In biofiltration of wastewater, air discharged from a treatment facility is passed through a damp porous membrane that causes contaminants to dissolve in water and be transformed into harmless products. Air discharge usually contains hydrogen sulfide, organic sulfides, and other volatile organic compounds (VOCS). For this experiment, it is desired to investigate the relationship between air inlet temperature and removal efficiency of porous membrane. The accompanying data on x = inlet temperature (°C) and y = removal efficiency (%) is shown below. Removal Removal Observation Temp "Observation Temp 1 7.68 98.09 17 8.55 98.27 2 6.51 98.25 18 7.59 98 3 6.49 97.82 19 6.94 98.09 4 5.48 97.82 20 8.31 98.25 5 6.57 97.82 21 10.5 98.41 6 10.13 97.93 22 16.02 98.51 15.71 98.38 23 17.83 98.71 16.77 98.89 24 17.03 98.79 9. 17.13 98.96 25 16.18 98.87 10 17.63 98.9 26 16.31 98.76 11 16.72 98.68 27 14.44 98.58 12 15.45 98.69 28 12.78 98.73 13 12.21 98.51 29 12.25 98.45 14 11.44 98.09 30 11.64 98.37 15 10.17 98.25 31 11.34 98.36 16 9.64 98.36 32 10.97 98.45
Using the data in Experiment 1, determine if there is sufficient evidence that inlet temperature could improve the removal efficiency of the membrane.
a. How does the inlet temperature affect the removal rate?
b. How strong is the relationship you concluded in 1a?
c. How significant is the relationship in 1a?
d. To a certain degree, can you estimate the expected removal rate with inlet temperature? Demonstrate this using an example. What is the typical
deviation from the estimate?
e. Using residual analysis, verify that your conclusion in ta-1c and your estimate in 1d are valid.
f. Using any methods discussed in Module 8, support your residual analysis in 1e by checking the normality of the errors in estimates.
EXPERIMENT 2: The specific objective of this experiment is to determine how the amount of rice hull ash (RHA) and concrete admixtures additions
affect concrete strength. After 28 days of curing, the data is collected and presented below.
Rice Hull Ash
Admixture
Concrete
Addition (%) Addition (%) Strength (MPa)
21.5
23.4
15
27.1
15
29.2
30
25.0
30
34.1
0.25
29.0
0.25
29.2
15
0.25
29.0
15
0.25
34.2
30
0.25
34.0
30
0.25
31.9
0.5
26.9
0.5
29.0
15
0.5
29.0
15
0.5
34.3
30
0.5
33.8
30
0.5
34.0
Transcribed Image Text:Using the data in Experiment 1, determine if there is sufficient evidence that inlet temperature could improve the removal efficiency of the membrane. a. How does the inlet temperature affect the removal rate? b. How strong is the relationship you concluded in 1a? c. How significant is the relationship in 1a? d. To a certain degree, can you estimate the expected removal rate with inlet temperature? Demonstrate this using an example. What is the typical deviation from the estimate? e. Using residual analysis, verify that your conclusion in ta-1c and your estimate in 1d are valid. f. Using any methods discussed in Module 8, support your residual analysis in 1e by checking the normality of the errors in estimates. EXPERIMENT 2: The specific objective of this experiment is to determine how the amount of rice hull ash (RHA) and concrete admixtures additions affect concrete strength. After 28 days of curing, the data is collected and presented below. Rice Hull Ash Admixture Concrete Addition (%) Addition (%) Strength (MPa) 21.5 23.4 15 27.1 15 29.2 30 25.0 30 34.1 0.25 29.0 0.25 29.2 15 0.25 29.0 15 0.25 34.2 30 0.25 34.0 30 0.25 31.9 0.5 26.9 0.5 29.0 15 0.5 29.0 15 0.5 34.3 30 0.5 33.8 30 0.5 34.0
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