Example of data table: Student Number Red Card Rating / A Black Card Rating / B. Example of provided rating paper: Student Number: 03 A: /10 B: /10

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1 The purpose of my experiment is to see if adding sugar to milk affects the taste and to investigate if sweetened or unsweetened milk is preferred for year ten and twelve students. Question: Is there any difference in standard dark blue top milk taste rating of 1-10 between an untreated sample and a treated sample of one teaspoon of caster sugar added to the milk for a year ten and twelve Pakuranga College mathematics class students? For my experiment I will use two three-litre bottles of Anchor brand standard dark blue top milk which will be divided into sixty identical foam cups with measured 100mL of milk in each so there are two cups of milk per student. One teaspoon of Chelsea caster sugar will be added to thirty cups and separated from the non-treated samples on our desk by placing on different desks with a sheet of A3 white paper with a A and another sheet with a B to indicate clearly to participants the separate samples. I will use twenty five students for this taste experiment. For each data recording I will ask the student to drink a sample of milk and decide on a rating between 1 to 10. They have to drink the whole sample before providing their rating. Each student will try both milk samples and the data will be recorded on a table together so they can be easily compared when analysing the results, along with their test number. Rating must be recorded from the student before they leave the experiment desk, and the student cannot describe the taste of the milk or share their rating as it could influence another student s rating results. We will ask the student if they are allowed milk before letting them participate due to medical and ethical reasons. The student will be given their milk samples one at a time. Their first sample will be determined by if the playing card selected is red or black suit (there will be an even split with the number of playing cards being equal to the number of student participants) Red cards will be representing the treated milk / A sample and black cards will be representing the untreated milk / B sample. Once the student has drunk the whole sample they will be asked to give a numerical rating between 1 to 10, with 1 being bad and 10 being good. The student will write their ratings on the provided paper which I will then transfer into the data recording table (example below). The student will then be given their second sample of milk and asked to give another rating which will be recorded on the same piece of paper and recorded in the same table next to the previous rating as this is a paired experiment. One teaspoon of sugar makes the milk taste sweeter so if the addition of sugar affects the student s taste and makes a difference in rating there will be enough data to see a difference. Example of data table: Student Number Red Card Rating / A Black Card Rating / B Example of provided rating paper: Student Number: 03 A: /10 B: /10 Other variables that could affect my experiment are; personal preference, influenced rating, gender, medical and ethical reasons, and hunger/thirst. Personal taste preferences will affect our recorded data as some students will prefer unsweetened or sweetened foods, and may have a strong preference of natural or flavoured milk, but since their ratings for both samples are recorded in pairs I will be able to see when this has occurred. Some year ten/twelve students will enjoy milk and some will dislike the taste as a general taste preference so the ratings from them will be higher/lower based on their like/dislike for milk. If students share their given ratings with peers then this could influence their ratings which would not reflect their personal taste and preference. Gender could affect my experiment as boys may like sweeter milk more than girls, or vice versa, and if the class has an uneven gender split then this variable

2 could affect my experiment. It is possible that a student may not be able to participate due to medical or religious reasons such as lactose intolerance or dietary requirements. Hunger/thirst is likely to affect my experiment as since the experiment is happening after lunch, if the student is still hungry/thirsty they are likely to give a higher rating, whereas if they are full from their lunch then they will probably give a lower rating. My research into this topic shows that 80% of our foods have added sugar to appeal to the consumer, even within foods which are commonly perceived as healthy (That Sugar Movie official trailer I think that my experiment will show how addition of sugar appeals to youth and their preference for sweeter foods, as the 2002 National Children s Nutritional Survey documented that the average daily intake or table sugar/sucrose for males is 17 teaspoons and females have 15 teaspoons of sugar daily ( which contrinuted 20% of their daily energy intake. The table below from the Ministry of Health ( system/files/documents/publications/food-nutrition-guidelines-healthy-children-young-peoplebackground-paper-feb15.pdf) shows high percentages of intake of high fat/sugar foods in adolescent diets, which demonstrates how adolescents have a taste preference for sweet foods. Anchor blue top milk has 4.8 grams of carbohydrate-sugars per 100mL. 1 level teaspoon of Chelsea caster sugar is 4g of sugar which is 16 calories. Adding a teaspoon of sugar to the milk will almost double the sugar content and the energy will rise from 260 kilojoules to 328 kilojoules.

3 Student Number Red Card Rating Sample A Black Card Rating Sample B Rating Difference

4 Sample A Treated Milk Results: 1 teaspoon of sugar added

5 Sample B Untreated Milk Results: standard milk Rating Difference

6 Paired Experiment Comparison

7 Sample A milk with the treatment of added sugar has a median of 9 which is a very high score for a 1-10 taste rating, with 56% of participants giving a rating of 9 or 10 (modes). Sample B of untreated milk has a lower median at 6 with 56% of participants giving a taste rating from 4 to 6 and only 12% giving a rating of 9 or 10. The mean of Sample A milk is which is higher than Sample B mean of The inter-quartile range (IQR) of sugar treated Sample A milk is 2.5 as the upper quartile is at the maximum rating of 10 and the lower quartile is at 7.5, demonstrating that a majority of ratings from the 25 students were high ratings. Sample B untreated milk has a similar interquartile range at 2 but the upper quartile is 7 and the lower quartile is 5, showing that students generally rated the untreated milk lower and with a fairly average score compared to the high scoring treated sugar-added milk. The range of Sample A data is smaller than Sample B. Sample A range is 6 which shows that no students rated lower than 4, whereas Sample B results have a range of 9 as there were ratings from 1-10 as Sample B received a score for all possible options from the Pakuranga College mathematics students who completed this experiment. The standard deviation of Sample A treated milk is which is lower than Sample B untreated milk with the standard deviation of which further communicates how Sample A has a smaller spread of data with less variation and dispersion than Sample A untreated milk which received more varied scores and has a larger spread of data. Sample A treated milk is left/negative skewed as the tail shows that the mean (8.3333) is less than the mode (9 and 10) and the median (9). The median is the same as the lower-rating mode (9). The mode for Sample A are 9 and 10 as they both received 7 ratings from year 10/12 students. Sample B is symmetrical as the median of 6 and mean of are similar.

8 The data is clustered around the IQR in the middle of the rating spread and then there are distributed ratings both above and below which creates a symmetric dot plot. There are no unusual features in either sets of the paired experiment data. Although 88% of Sample A ratings are 7-10, the other 12% make a small cluster at 4-5. Sample B untreated milk ratings are spread out as at least one student gave a rating at each number between the 1-10 rating options, so no outliers are present. There is no evidence of bi-modal data. The above graph includes an informal confidence (IC) for the median which represents the true median. Since 0 isn t within the IC interval, this indicates that there was a difference in ratings for sample A and sample B of the milk experiment. Due to the small sample size of only 25 students participating in our taste test of sugar milk vs untreated milk, the blue bar above is big with a range of 1.1 to 2.9. If we could conduct an experiment which involved more students, the range would decrease, allowing us to calculate a more precise true median. If we could test the all the year ten mathematics students, all the students at Pakuranga College, or a national milk test to investigate how sugar addition to foods affects adolescents preference between a treated sugar-added sample and an untreated sample.

9 The purpose of my experiment was to see if adding sugar to milk affected the taste of milk and to investigate if sweetened or unsweetened milk was preferred for year ten and twelve students. The question was: Is there any difference in standard dark blue top milk taste rating of 1-10 between an untreated sample and a treated sample of one teaspoon of caster sugar added to the milk for a year ten and twelve Pakuranga College mathematics students? Through a practical experiment to collect the data and analysing this data using graphs and statistical information, I found that sweetened milk was prefered by the participating population, that adding one teaspoon of caster sugar to a 100mL cup of standard dark blue top milk generally received higher taste ratings compared to the untreated B sample, as seen in the data analysis previously discussed. An American research article in The Journal of School Nursing ( 24/1/3.short?rss=1&ssource=mfc) discusses how soft drink consumption by adolescents have increased by 300% in the last twenty years, and that 56-85% of students consume at least one soft drink daily in America, demonstrating how adolescents like sugary beverages. In a background paper written by New Zealand Ministry of Health regarding nutrition guidelines for healthy adolescents ( fe/$FILE/foodnutritionguidelines-adolescents.pdf), they claim that while New Zealand adolescents appear to have intakes within the recommended range for carbohydrate, a high proportion of the carbohydrates are from refined sugars, especially sucrose as carbonated high-sugar drinks are regularly consumed by a majority of the adolescent population. Excessive sugar intake is realted to a range of health effects; cardiovasular disease, type-2 diabetes, raised blood pressure, weight gain, obesity, oral health, etc. A comprehensive article ( refers to a review in 2006 which through observational studies found a positive relationship between sugar-sweetened beverages, unhealthy weight, fat accumulation, and related health issues. The most recent national survey shows that 26% of adolescent total sugar intake is from sugar-sweetened beverages. This information explains why the treated sample with the added teaspoon of sugar was generally prefered by the tested students, but demonstrates that although sweetened milk is preferred by participating adolescents, it is not a healthy option and should not be encouraged. Milk has many benefits; calcium strengthens bones, muscle contraction improvement, source of protein, vitamin D intake, and cognitive performance improvement, so a moderated intake is encouraged, whereas addition of sugar is unnecessary and unhealthy. If I completed this experiment again, I would like to have access to a larger group of students to participate so the sample size is larger as this would allow us to have clearer data summaries and make stronger claims regarding preference and difference between treated and untreated milk. We could improve the method of how the student completed the experiment as confusion and disorganisation was evident. I would like to continue using the card method to decide which sample they tried first as it meant there was half the students trying sample A first and the other half trying B first which made the testing conditions more fair, but the system wasn t executed well which caused confusion for us running it and those participating. I would provide their data recording sheet first, explain how the taste rating worked, and then give them a sample based on the card which only I would use, rather than giving the student the card. This would make the system flow better and make more sense to the participant. I would also like to improve the experiment by only conducting this experiment at the time as other experiments would influence the ratings received due to aftertaste and previous experiment preferences (i.e. the student likes coke more than milk) as these factors probably had an affect on our data due to the number of experiments the students were

10 participating in. If we could run our experiment separately to others it would be a strong improvement as the data would be less affected by outside influences.