No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 WID 9005 9005 9005 9005 5258 5258 1329 1329 1329 6727 6727 4661 4661 4661 6528 6528 0771 0771 5163 5163 8225 8225 2713 2713 3946 3946 3946 9023 9023 1154 1154 Triangle 0 1 1 0 1 1 1 0 1 0 0 0 1 1 1 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 Dual comparison 0 1 1 1 1 1 1 0 1 0 0 1 0 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 1 1 1 3-AFC 0 1 0 1 1 0 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 Paired comparison 0 1 0 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0=wrong answers 1=correct answers 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 1154 9062 9062 9062 9062 4392 4392 9026 9026 2228 2228 6211 6211 7932 7932 7617 7617 1487 1487 1487 1487 1412 1412 8711 8711 8711 5786 5786 5786 9422 9422 5452 0 1 0 1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 0 1 1 0 1 0 1 0 0 0 1 0 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 0 1 0 0 0 1 0 1 1 0 0 1 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 5452 5452 8529 8529 8529 8529 1931 1931 1931 1931 1931 8605 8605 8023 8023 8023 8023 4975 4975 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 1 1 1 0 1 0 1 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 1 1 0 0 1 1 1 1 0 1 0 0 1 1 1 0 1 1 0 1 1 0 1 1 1 0 1 1 1 0 0 1 1 1 1 0 1 1 p(observed) C – Correct Judgements z-Value Minimum number of correct judgements D – # of discriminators D/n(n=Total number of panelists) Triangle Dual Standard 3-AFC Paired Comparison 40/82 54/82 54/82 62/82 40 54 54 62 2,8502 2,7607 6,1298 4,5276 35 48 35 48 19 26 40 42 19/82 26/82 40/82 42/82 p(chance)Chance probability Also q = 1-p Triangle Dual Standard 3-AFC 1/3 1/2 1/3 0,6666667 0,5 0,6667 Paired Comparison 1/2 0,5 Note : Z-value for all test is greater than the Z-critical value which says the two products are significantly different for a given test m We can also note that C – correct judgments is greater than the minimum number of correct judgments for all 3 tests which s P*N C-P*N C-P*N/Q 27,33 12,67 19 41 13 26 27,33 26,67 40 41 21 42 dgments for all 3 tests which shows that the panelists were able to differentiate between the products and that they are significantly diff d that they are significantly different. Lab 2 – Comparison of Discrimination Test Methods Notes: Students are responsible for preparing and conducting the tests, then entering data into a shared excel worksheet. For this lab, you’ll work as both an experimenter and an evaluator. (You may have somebody else set up the tests for you so that you can do the evaluation). Each student needs to upload at least TWO subjects’ data (including data from yourself). Please take photos of your lab set ups and include them in your lab report. • Data Upload Due: 11:59 PM CST 10/05/2023 • Report Due: 11:59 PM CST 10/12/2023 Instructions For this lab, you will have to closely follow the instructions in the lab manuals (page 27) to conduct 4 discrimination tests: Triangle, Dual Standard, 3-AFC, and Paired Comparison (or 2-AFC). Below are some key things. • Materials o Kool-aid Black Cherry Drink Mix Unsweetened 0.13 oz. Packet (2 packets) o Sucrose/ Commercial sugar o Distilled water/ Any odorless water o 1 oz. plastic cups (24 cups) o Rinsing cups (2 cups) and spitting cups (2 cups) o Napkins and unsalted saltine crackers • Equipment o Label gun or other means (blank labels-hand writing) of affixing 3-digit random code labels to cups. o Balance for weighing sucrose o Serving tray (optional) • Preparation Procedures o Prepare two test solutions with different level of added sucrose ▪ Dissolve one sachet of Kool-aid in about 1.5 L of water and add 180 g sugar. Stir until dissolved and add water to achieve a final total volume of 2 L. Final concentration = 9 % wt/vol. ▪ Dissolve one sachet of Kool-aid in 1.5 L of water and add 200 g sugar. Stir until dissolved and add water to achieve a final total volume of 2 L. Final concentration = 10 % wt/vol. o For each evaluator, 12 cups (1 oz. cup) of solutions are needed for the four sets of tests. The suggested sample codes and the corresponding products are shown in the table below. 1 Sample Code Test product Triangle Test ( give any three, ask to choose which one is different, see sample ballots in lab manuals) 469 Powdered drink mix at 9% sucrose wt/vol 642 Powdered drink mix at 9% sucrose wt/vol 849 Powdered drink mix at 10% sucrose wt/vol 703 Powdered drink mix at 10% sucrose wt/vol Dual Standard Test (ask to match to reference, see sample ballots in lab manuals ) Ref A Powdered drink mix at 9% sucrose wt/vol 811 Powdered drink mix at 9% sucrose wt/vol Ref B Powdered drink mix at 10% sucrose wt/vol 837 Powdered drink mix at 10% sucrose wt/vol 3-AFC (ask to choose which one is sweetest, see sample ballot in lab manuals) 679 Powdered drink mix at 9% sucrose wt/vol 995 Powdered drink mix at 9% sucrose wt/vol 685 Powdered drink mix at 10% sucrose wt/vol 2-AFC (ask to choose which one is sweeter, see sample ballot in lab manuals) 824 Powdered drink mix at 9% sucrose wt/vol 762 Powdered drink mix at 10% sucrose wt/vol • Evaluation For each evaluator: o Perform tests as instructed on the individual ballots (you can find the ballots on page 31 of lab manual) in the following order: Triangle, dual standard, 3-AFC and paired comparison (2-AFC). o Do one test at a time. You may instruct the evaluator to have 1 minute break for palate cleansing between tests. • Data Collection and Report o Data Upload: go to Canvas-Module- Lab 2- Lab 2 Data Upload, to find the shared file link o Report: you’ll need to write an industrial report for this lab. Please follow the guidelines in your lab exercise book (page 27). 2 LAB manual reporting (guidelines on report generation) Page 28 & 29: Sample report from lab manual: Sample Student report: Mr/Ms …. to Mr/Ms …. 10/05/2021 Comparison of Discrimination Methods From: Mr/Ms……, Sensory Scientist To: Mr/Ms……, R & D Manager Date: Oct 05, 2021 Background Consumers are looking for low-calorie beverages because added sugar in beverages has become a health concern. The goal of this study was to see if a 10% reduction in the sugar level of our purplestuff drink mix made a noticeable difference in taste. The relative sensitivity of different testing methods was a secondary question. Conclusions: The panelists were able to identify the sugar reduction in the beverage. Paired comparison and 3 AFC tests were more sensitive compared to the dual standard and triangle test. Z-value for all tests are greater than the Z-critical value which says, two products are significantly different for a given test method. We can also note that C – correct judgments is greater than the minimum number of correct judgments for all 3 tests which shows that the panelists were able to differentiate between the products and that they are significantly different. Recommendations The reduced-level formula should be tested for consumer acceptance. The sweetness levels can be increased using other sweeteners to bridge the gap. Samples Sample Code Test product Triangle Test – choose which one is different out of three samples 642 Powdered drink mix at 9% sucrose wt/vol 849 Powdered drink mix at 10% sucrose wt/vol 703 Powdered drink mix at 10% sucrose wt/vol Dual Standard Test (match to reference samples) Ref A Powdered drink mix at 9% sucrose wt/vol 811 Powdered drink mix at 9% sucrose wt/vol Ref B Powdered drink mix at 10% sucrose wt/vol 837 Powdered drink mix at 10% sucrose wt/vol 3-AFC – choose which one is sweetest 679 Powdered drink mix at 9% sucrose wt/vol 995 Powdered drink mix at 9% sucrose wt/vol 685 Powdered drink mix at 10% sucrose wt/vol 2-AFC / Paired comparison – choose which one is sweeter 824 Powdered drink mix at 9% sucrose wt/vol 762 Powdered drink mix at 10% sucrose wt/vol Test Methods Null Hypothesis Alt Hypothesis Triangle p=1/3 p>1/3 Duo-trio p=1/2 p>1/2 Paired Comparison p=1/2 p>1/2 Rated Difference 9% = 10% 9% ≠ 10% Results: p(observed) C – Correct Judgements z-Value Minimum number of correct judgements D – # of discriminators D/n(n=Total number of panelists) p(chance) Also q = 1-p Triangle 40/82 40 2.8502 35 Dual Standard 54/82 54 2.7607 48 3-AFC 54/82 54 6.1298 35 Paired Comparison 62/82 62 4.5276 48 19 19/82 26 26/82 40 40/82 42 42/82 Triangle 1/3 0.666667 Dual Standard 1/2 0.5 3-AFC Paired Comparison 1/3 1/2 0.666667 0.5 Panelists 82 employee volunteers from the general taste testing pool (untrained). Date of work Request: Sep. 27, 2021 Date Conducted: Oct. 01, 2021 No. WID Triangle Dual comparison 3-AFC Paired comparison 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 7691 7691 8705 8705 3850 3850 3776 3776 3776 4590 4590 2276 2276 7227 8287 8287 4689 4689 3781 3781 7137 7137 2786 2786 1836 1836 9896 9896 0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 1 1 1 1 1 0 1 0 0 1 0 1 1 1 1 0 1 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 1 1 1 1 1 1 1 0 1 0 0 1 1 1 0 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 3449 3449 6141 6141 5188 5188 6898 6898 5512 5512 5602 5602 8849 8849 5314 5314 5314 0594 0594 0594 0844 0844 0844 1522 1522 5785 5785 5785 4258 4258 4258 9475 1 0 0 1 0 0 0 1 1 0 1 1 1 1 1 0 1 0 1 1 1 1 0 1 0 0 1 1 1 0 0 1 1 1 1 0 0 1 1 0 1 1 0 1 1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 0 1 1 1 0 1 1 1 1 1 1 0 0 1 0 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 0 1 1 0 0 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 61 62 63 64 65 66 67 68 69 70 71 72 73 9475 2454 2454 5195 5195 5195 1426 1426 3041 3041 3041 3228 3228 1 0 0 1 1 0 0 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0=wrong answers 1=correct answers Summary table p(observed) C – Correct Judgements z-Value Minimum number of correct judgements D – # of discriminators D/n(n=Total number of panelists) p(chance)Chance probability Also q = 1-p I have done it for the Triangle test for your reference. Try doing it for other tests Solving the equation for finding the Z value: For Triangle test calculating Z value= Z= Note: Solving the equation for finding the D= For Triangle test calculating D (# of discriminators)= D= Summary table Triangle 38/73 38 3,26904326 31 21 21/73 Triangle 1/3 0,66667 ur reference. Try doing it for other tests (38-(73*(1/3))-.5)/(SQRT(73*(1/3)*(1-(1/3)))) 3,269043 You’ll compare the calculated z-value to the critical z-value (1.645). If it’s higher than the critical z-value (1.645) then the two products are significantly different for a given test method or you can compare the C with the “minimum no of correct judgments” from the table in the appendix. If C is higher than the minimum number of correct judgements, it means panelists were able to differentiate between the products and that they are significantly different. (C – p*n)/(1-p), where p = p(chance) provided for each test method (38-(1/3)*73)/(1-1/3) 21 Dual Standard 3-AFC Dual Standard 3-AFC 1/2 1/3 0,50000 0,66667 For Data analysis: Paired Comparison p (observed) = # of correct answers/total # of panelists = (C/n) C = # of correct answers Z-value = You should be using the formula provided in the lab manual (p Z-value is for statistical analysis. You’ll compare the calculated z-value to Z-value can be used to see how far your result is from the mean value Paired Comparison 1/2 0,50000 Minimum number of correct judgements = the table provided in the sta D = number of discriminators = (C – p*n)/(1-p), where p = p(chance) prov D/n = Estimated proportion of discriminators If D is negative or equal to 0, then D/n also becomes 0. e calculated z-value to the critical z-value (1.645). If it’s higher than the critical z-value (1.645) then the two products are signif ble provided in the statistical appendix; look for tabled value based on “n” and probability level of 0.05 (“Discrimination testing n the two products are significantly different for a given test method or you can compare the C with the “minimum no of corre th the “minimum no of correct judgments” from the table in the appendix. If C is higher than the minimum number of correct minimum number of correct judgements, it means panelists were able to differentiate between the products and that they are e products and that they are significantly different. LAB manual reporting (guidelines on report generation) Page 28 & 29: Sample report from lab manual: Sample Student report: Mr/Ms …. to Mr/Ms …. 10/05/2021 Comparison of Discrimination Methods From: Mr/Ms……, Sensory Scientist To: Mr/Ms……, R & D Manager Date: Oct 05, 2021 Background Consumers are looking for low-calorie beverages because added sugar in beverages has become a health concern. The goal of this study was to see if a 10% reduction in the sugar level of our purplestuff drink mix made a noticeable difference in taste. The relative sensitivity of different testing methods was a secondary question. Conclusions: The panelists were able to identify the sugar reduction in the beverage. Paired comparison and 3 AFC tests were more sensitive compared to the dual standard and triangle test. Z-value for all tests are greater than the Z-critical value which says, two products are significantly different for a given test method. We can also note that C – correct judgments is greater than the minimum number of correct judgments for all 3 tests which shows that the panelists were able to differentiate between the products and that they are significantly different. Recommendations The reduced-level formula should be tested for consumer acceptance. The sweetness levels can be increased using other sweeteners to bridge the gap. Samples Sample Code Test product Triangle Test – choose which one is different out of three samples 642 Powdered drink mix at 9% sucrose wt/vol 849 Powdered drink mix at 10% sucrose wt/vol 703 Powdered drink mix at 10% sucrose wt/vol Dual Standard Test (match to reference samples) Ref A Powdered drink mix at 9% sucrose wt/vol 811 Powdered drink mix at 9% sucrose wt/vol Ref B Powdered drink mix at 10% sucrose wt/vol 837 Powdered drink mix at 10% sucrose wt/vol 3-AFC – choose which one is sweetest 679 Powdered drink mix at 9% sucrose wt/vol 995 Powdered drink mix at 9% sucrose wt/vol 685 Powdered drink mix at 10% sucrose wt/vol 2-AFC / Paired comparison – choose which one is sweeter 824 Powdered drink mix at 9% sucrose wt/vol 762 Powdered drink mix at 10% sucrose wt/vol Test Methods Null Hypothesis Alt Hypothesis Triangle p=1/3 p>1/3 Duo-trio p=1/2 p>1/2 Paired Comparison p=1/2 p>1/2 Rated Difference 9% = 10% 9% ≠ 10% Results: p(observed) C – Correct Judgements z-Value Minimum number of correct judgements D – # of discriminators D/n(n=Total number of panelists) p(chance) Also q = 1-p Triangle 40/82 40 2.8502 35 Dual Standard 54/82 54 2.7607 48 3-AFC 54/82 54 6.1298 35 Paired Comparison 62/82 62 4.5276 48 19 19/82 26 26/82 40 40/82 42 42/82 Triangle 1/3 0.666667 Dual Standard 1/2 0.5 3-AFC Paired Comparison 1/3 1/2 0.666667 0.5 Panelists 82 employee volunteers from the general taste testing pool (untrained). Date of work Request: Sep. 27, 2021 Date Conducted: Oct. 01, 2021 LAB manual reporting (guidelines on report generation) Page 28 & 29: Sample report from lab manual: Sample Student report: Mr/Ms …. to Mr/Ms …. 10/05/2021 Comparison of Discrimination Methods From: Mr/Ms……, Sensory Scientist To: Mr/Ms……, R & D Manager Date: Oct 05, 2021 Background Consumers are looking for low-calorie beverages because added sugar in beverages has become a health concern. The goal of this study was to see if a 10% reduction in the sugar level of our purplestuff drink mix made a noticeable difference in taste. The relative sensitivity of different testing methods was a secondary question. Conclusions: The panelists were able to identify the sugar reduction in the beverage. Paired comparison and 3 AFC tests were more sensitive compared to the dual standard and triangle test. Z-value for all tests are greater than the Z-critical value which says, two products are significantly different for a given test method. We can also note that C – correct judgments is greater than the minimum number of correct judgments for all 3 tests which shows that the panelists were able to differentiate between the products and that they are significantly different. Recommendations The reduced-level formula should be tested for consumer acceptance. The sweetness levels can be increased using other sweeteners to bridge the gap. Samples Sample Code Test product Triangle Test – choose which one is different out of three samples 642 Powdered drink mix at 9% sucrose wt/vol 849 Powdered drink mix at 10% sucrose wt/vol 703 Powdered drink mix at 10% sucrose wt/vol Dual Standard Test (match to reference samples) Ref A Powdered drink mix at 9% sucrose wt/vol 811 Powdered drink mix at 9% sucrose wt/vol Ref B Powdered drink mix at 10% sucrose wt/vol 837 Powdered drink mix at 10% sucrose wt/vol 3-AFC – choose which one is sweetest 679 Powdered drink mix at 9% sucrose wt/vol 995 Powdered drink mix at 9% sucrose wt/vol 685 Powdered drink mix at 10% sucrose wt/vol 2-AFC / Paired comparison – choose which one is sweeter 824 Powdered drink mix at 9% sucrose wt/vol 762 Powdered drink mix at 10% sucrose wt/vol Test Methods Null Hypothesis Alt Hypothesis Triangle p=1/3 p>1/3 Duo-trio p=1/2 p>1/2 Paired Comparison p=1/2 p>1/2 Rated Difference 9% = 10% 9% ≠ 10% Results: p(observed) C – Correct Judgements z-Value Minimum number of correct judgements D – # of discriminators D/n(n=Total number of panelists) p(chance) Also q = 1-p Triangle 40/82 40 2.8502 35 Dual Standard 54/82 54 2.7607 48 3-AFC 54/82 54 6.1298 35 Paired Comparison 62/82 62 4.5276 48 19 19/82 26 26/82 40 40/82 42 42/82 Triangle 1/3 0.666667 Dual Standard 1/2 0.5 3-AFC Paired Comparison 1/3 1/2 0.666667 0.5 Panelists 82 employee volunteers from the general taste testing pool (untrained). Date of work Request: Sep. 27, 2021 Date Conducted: Oct. 01, 2021 No. WID Triangle Dual comparison 3-AFC Paired comparison 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 7691 7691 8705 8705 3850 3850 3776 3776 3776 4590 4590 2276 2276 7227 8287 8287 4689 4689 3781 3781 7137 7137 2786 2786 1836 1836 9896 9896 0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 1 1 1 1 1 0 1 0 0 1 0 1 1 1 1 0 1 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 1 1 1 1 1 1 1 0 1 0 0 1 1 1 0 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 3449 3449 6141 6141 5188 5188 6898 6898 5512 5512 5602 5602 8849 8849 5314 5314 5314 0594 0594 0594 0844 0844 0844 1522 1522 5785 5785 5785 4258 4258 4258 9475 1 0 0 1 0 0 0 1 1 0 1 1 1 1 1 0 1 0 1 1 1 1 0 1 0 0 1 1 1 0 0 1 1 1 1 0 0 1 1 0 1 1 0 1 1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 0 1 1 1 0 1 1 1 1 1 1 0 0 1 0 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 0 1 1 0 0 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 61 62 63 64 65 66 67 68 69 70 71 72 73 9475 2454 2454 5195 5195 5195 1426 1426 3041 3041 3041 3228 3228 1 0 0 1 1 0 0 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0=wrong answers 1=correct answers Summary table p(observed) C – Correct Judgements z-Value Minimum number of correct judgements D – # of discriminators D/n(n=Total number of panelists) p(chance)Chance probability Also q = 1-p I have done it for the Triangle test for your reference. Try doing it for other tests Solving the equation for finding the Z value: For Triangle test calculating Z value= Z= Note: Solving the equation for finding the D= For Triangle test calculating D (# of discriminators)= D= Summary table Triangle 38/73 38 3.26904326 31 21 21/73 Triangle 1/3 0.66667 ur reference. Try doing it for other tests (38-(73*(1/3))-.5)/(SQRT(73*(1/3)*(1-(1/3)))) 3.269043 You’ll compare the calculated z-value to the critical z-value (1.645). If it’s higher than the critical z-value (1.645) then the two products are significantly different for a given test method or you can compare the C with the “minimum no of correct judgments” from the table in the appendix. If C is higher than the minimum number of correct judgements, it means panelists were able to differentiate between the products and that they are significantly different. (C – p*n)/(1-p), where p = p(chance) provided for each test method (38-(1/3)*73)/(1-1/3) 21 Dual Standard 3-AFC Dual Standard 3-AFC 1/2 1/3 0.50000 0.66667 For Data analysis: Paired Comparison p (observed) = # of correct answers/total # of panelists = (C/n) C = # of correct answers Z-value = You should be using the formula provided in the lab manual (p Z-value is for statistical analysis. You’ll compare the calculated z-value to Z-value can be used to see how far your result is from the mean value Paired Comparison 1/2 0.50000 Minimum number of correct judgements = the table provided in the sta D = number of discriminators = (C – p*n)/(1-p), where p = p(chance) prov D/n = Estimated proportion of discriminators If D is negative or equal to 0, then D/n also becomes 0. e calculated z-value to the critical z-value (1.645). If it’s higher than the critical z-value (1.645) then the two products are signif ble provided in the statistical appendix; look for tabled value based on “n” and probability level of 0.05 (“Discrimination testing n the two products are significantly different for a given test method or you can compare the C with the “minimum no of corre th the “minimum no of correct judgments” from the table in the appendix. If C is higher than the minimum number of correct minimum number of correct judgements, it means panelists were able to differentiate between the products and that they are e products and that they are significantly different.
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