Figure 2 shows the results of the Tukey test to test pairwise differences at the significance level 0.05 for the additive model using design and region with regards to their impact on the survey responses.   Figure 2. (1st Image uploaded below)  Tukey test results showing pairwise factor level comparison with regards to impact on the survey responses. P adj shows the p value for each pairwise level comparison. P values with 0.0000000 indicate that the p value is < 0.00000001.   Considering a significance level of alpha = 0.05, select the correct statement below.   A.) For region, all pairwise Region levels differ from each other significantly with regards to survey responses.   B.) For design, all pairwise Design levels differ from each other significantly with regards to survey responses.   C.) The average survey response using Design 3 is 175.58 higher than the average survey response using Design 2.   D.) Designs 1 and 3 do not differ significantly; but Design 2 is significantly different than Design 1, and Design 2 is significantly different than Design 3 with regards to survey responses.     2.  Use the following description for Questions 2-3. Three different washing solutions are being compared to study their effectiveness in retarding bacteria growth in five-gallon milk containers.  The analysis is done in a laboratory, and only three trials can be run on any day.  Because days could represent a potential source of variability, the experimenter decides to use a model that reduces experimental error (and hence increases precision) by grouping days into blocks. Observations are taken for four days, values in table below show measurement of effectiveness (bacteria growth rate after using the solution) for each day and solution type.  (refer to 2nd Image Uploaded below) Question 2. Select the correct statement below.   A.) We should use a randomized block design using a two-way ANOVA model without an interaction term between Solution and Day and with a blocking factor for Days.   B.) We should use a randomized block design using a two-way ANOVA model without an interaction term between Solution and Day and with a blocking factor for Solution.   C.) We should use a randomized block design using a two-way ANOVA model without an interaction term between Solution and Day and with a blocking factor for Bacteria growth.   D.) We should use a one-way ANOVA using Solution as the Factor.     3.  Washington.csv: dataset below  Solution Day Result 1 1 13 1 2 22 1 3 18 1 4 39 2 1 16 2 2 24 2 3 17 2 4 44 3 1 5 3 2 4 3 3 1 3 4 22 Use the datafile washing.csv, which represents the study data discussed in Question 5. Save the data file in your local folder that you use as your R working directory. Keep in mind that when you download the datafile by clicking on the link "washing.csv" above BB Learn may change its name such as "washing(1).csv". Once you download it make sure to change the file name manually to "washing.csv" so that the code below runs without problems.   Analyze the data from this study (use a significance level α = 0.05) using the R code below and using the modeling approach you selected in Question 5. Based on the R output, which statement is correct? # read the data file and make sure the factors are recognized as factors by filling out the blank part in the code below wash <- read.csv("washing.csv", as.is =T) wash$             <- as.factor(wash$              ) wash$            <- as.factor(wash$               )   # run the model by filling out the blank part in the code below summary(aov(                          ))     A.) At the significance level 0.05, we fail to reject the null hypothesis that Days have an impact on retarding bacteria growth in milk containers.   B.) The degrees of freedom associated with testing the null hypothesis that different levels of the factor Solution have no impact on retarding bacteria growth in milk containers is 2.   C.) The degrees of freedom associated with testing the null hypothesis that different levels of the factor Day have no impact on retarding bacteria growth in milk containers is 6.   D.) The F statistic associated with testing the null hypothesis associated with the levels of Solution and their impact on retarding bacteria growth in milk containers is 42.71.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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  1.  

    Figure 2 shows the results of the Tukey test to test pairwise differences at the significance level 0.05 for the additive model using design and region with regards to their impact on the survey responses.
     
    Figure 2.

    (1st Image uploaded below) 


    Tukey test results showing pairwise factor level comparison with regards to impact on the survey responses. P adj shows the p value for each pairwise level comparison. P values with 0.0000000 indicate that the p value is < 0.00000001.

     
    Considering a significance level of alpha = 0.05, select the correct statement below.

      A.)

    For region, all pairwise Region levels differ from each other significantly with regards to survey responses.

      B.)

    For design, all pairwise Design levels differ from each other significantly with regards to survey responses.

      C.)

    The average survey response using Design 3 is 175.58 higher than the average survey response using Design 2.

      D.)

    Designs 1 and 3 do not differ significantly; but Design 2 is significantly different than Design 1, and Design 2 is significantly different than Design 3 with regards to survey responses.

 

 

2. 

Use the following description for Questions 2-3.
Three different washing solutions are being compared to study their effectiveness in retarding bacteria growth in five-gallon milk containers.  The analysis is done in a laboratory, and only three trials can be run on any day.  Because days could represent a potential source of variability, the experimenter decides to use a model that reduces experimental error (and hence increases precision) by grouping days into blocks. Observations are taken for four days, values in table below show measurement of effectiveness (bacteria growth rate after using the solution) for each day and solution type.

 (refer to 2nd Image Uploaded below)


Question 2.

Select the correct statement below.

  A.)

We should use a randomized block design using a two-way ANOVA model without an interaction term between Solution and Day and with a blocking factor for Days.

  B.)

We should use a randomized block design using a two-way ANOVA model without an interaction term between Solution and Day and with a blocking factor for Solution.

  C.)

We should use a randomized block design using a two-way ANOVA model without an interaction term between Solution and Day and with a blocking factor for Bacteria growth.

  D.)

We should use a one-way ANOVA using Solution as the Factor.

 

 

3. 

Washington.csv: dataset below 

Solution

Day Result
1 1 13
1 2 22
1 3 18
1 4 39
2 1 16
2 2 24
2 3 17
2 4 44
3 1 5
3 2 4
3 3 1
3 4 22

Use the datafile washing.csv, which represents the study data discussed in Question 5. Save the data file in your local folder that you use as your R working directory. Keep in mind that when you download the datafile by clicking on the link "washing.csv" above BB Learn may change its name such as "washing(1).csv". Once you download it make sure to change the file name manually to "washing.csv" so that the code below runs without problems.

 

Analyze the data from this study (use a significance level α = 0.05) using the R code below and using the modeling approach you selected in Question 5. Based on the R output, which statement is correct?


# read the data file and make sure the factors are recognized as factors by filling out the blank part in the code below
wash <- read.csv("washing.csv", as.is =T)
wash$             <- as.factor(wash$              )
wash$            <- as.factor(wash$               )
 
# run the model by filling out the blank part in the code below
summary(aov(                          ))
 

  A.)

At the significance level 0.05, we fail to reject the null hypothesis that Days have an impact on retarding bacteria growth in milk containers.

  B.)

The degrees of freedom associated with testing the null hypothesis that different levels of the factor Solution have no impact on retarding bacteria growth in milk containers is 2.

  C.)

The degrees of freedom associated with testing the null hypothesis that different levels of the factor Day have no impact on retarding bacteria growth in milk containers is 6.

  D.)

The F statistic associated with testing the null hypothesis associated with the levels of Solution and their impact on retarding bacteria growth in milk containers is 42.71.

Days
4
3
Solution
1
2
13
22
18
39
16
24
17
44
5
4
1
22
123
Transcribed Image Text:Days 4 3 Solution 1 2 13 22 18 39 16 24 17 44 5 4 1 22 123
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = Response - Design + Region, data = ads)
SDesign
p adj
1wr
2-1 167.916667 130.03784 205.79549 0.0000000
-7.666667 -45. 54 549 30. 21216 0. 8723492
3-2 -175. 583333 -213.46216 -137.70451 0.0000000
diff
upr
3-1
SRegion
p adj
27.75772 124.2422836 0. 0009529
SE-NE -49. 000000 -97.24228 -0.7577164 0.0454415
19.42438 115. 9089503 0. 0033716
diff
1wr
upr
NW-NE
76. 000000
SW-NE
67.666667
SE-NW -125.000000 -173.24228 -76. 7577164 0.0000005
39. 9089503 0.9651365
68.42438 164.9089503 0.0000016
-8. 333333 -56. 57562
116. 666667
SW-NW
SW-SE
Transcribed Image Text:Tukey multiple comparisons of means 95% family-wise confidence level Fit: aov(formula = Response - Design + Region, data = ads) SDesign p adj 1wr 2-1 167.916667 130.03784 205.79549 0.0000000 -7.666667 -45. 54 549 30. 21216 0. 8723492 3-2 -175. 583333 -213.46216 -137.70451 0.0000000 diff upr 3-1 SRegion p adj 27.75772 124.2422836 0. 0009529 SE-NE -49. 000000 -97.24228 -0.7577164 0.0454415 19.42438 115. 9089503 0. 0033716 diff 1wr upr NW-NE 76. 000000 SW-NE 67.666667 SE-NW -125.000000 -173.24228 -76. 7577164 0.0000005 39. 9089503 0.9651365 68.42438 164.9089503 0.0000016 -8. 333333 -56. 57562 116. 666667 SW-NW SW-SE
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