Results
Figure 1: Energy and macronutrient content of Cheese and Bacon Balls, Macadamia Nut and Popcor
Food item Energy (kJ) Protein
(g) Fat (total) (g) Fat (saturated) (g) Carbohydrate
(g) Sugars
(g) Sodium
(mg)
Cheese and Bacon balls 2270 6.5 33.2 16.4 53.7 3.3 667
Macadamia nut 3040 11.2 72.2 12.1 8.0 4.3 2.4
Popcorn 1910 11.7 17.5 1.6 57.3 0.1 494
Data to be recorded Cheese and Bacon Balls Trial 1 Trial 2 Trial 3
Mass of food initial(g) 2.69g 3.08g 1.90g
Mass of food final(g) 0.23g 0.26g 0.17g
Mass of food combusted(g) 2.46g 2.82g 1.73g
Mass of water (ml) 10mL 10mL 10mL
Final water temperature (°C) 57® 71® 68®
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Initial water temperature(°C) 23® 25® 26®
Temperature change(°C) 34® 46® 42® Figure 2: Raw Data of Cheese and Bacon Balls
Data to be recorded Macadamia Nut Trial 1 Trial 2 Trial 3
Mass of food initial(g) 3.33g 3.61g 3.50g
Mass of food final(g) 3.00g 3.36g 2.93g
Mass of food combusted(g) 0.33g 0.25g 0.51g
Mass of water (ml) 10mL 10mL 10mL
Final water temperature (°C) 45® 43® 53®
Initial water temperature(°C) 23® 25® 25®
Temperature change(°C) 22® 18® 28®
Figure 3: Raw Data of Macadamia Nut
Figure 4: Raw data of Popcorn
Data to be recorded Popcorn Trial 1 Trial 2
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In figure 2, the class mean calculated was 147.8kJ. The difference between the two measurements is 2,122.2kJ. This shows how low the accuracy for this experiment was. The macadamia nuts had a true energy value of 3040kJ per 100g. Looking back at figure 2, the class mean calculated was 224.4kJ which leaves a difference of 2,815.6kJ. Once again, a low accuracy. Lastly, the popcorn had a true energy value of 1910kJ. The class mean equalled to 144.1kJ. The difference between the class mean and the true value is 1,765.9kJ which shows this experiment being low in
In the experiment, 0.436 Calories per gram were found when dividing the average heat per mass of food by 1000. The standard deviation proved that this number can either be moved up 0.082 Cal/g or down. This is nowhere near the 3.2 Calories per gram which appeared on the label
The data we gathered was tested to be as accurate as possible. Our prediction on the solvents did not support our data that we collected. The cause of this could be due to human error when washing the beets or the cutting of the beets. The beets were not perfectly cut the same size, so some beet pieces were bigger than others which can affect the final the final result. We followed each step and followed the time limits cautiously. I can say if we were to redo the experiment our results would be similar because we would attempt to do the experiment as close as we did the first
Discussion: The percent of errors is 59.62%. Several errors could have happened during the experiment. Weak techniques may occur.
In this experiment, there were several objectives. First, this lab was designed to determine the difference, if any, between the densities of Coke and Diet Coke. It was designed to evaluate the accuracy and precision of several lab equipment measurements. This lab was also designed to be an introduction to the LabQuest Data and the Logger Pro data analysis database. Random, systematic, and gross errors are errors made during experiments that can have significant effects to the results. Random errors do not really have a specific cause, but still causes a few of the measurements to either be a little high or a little low. Systematic errors occur when there are limitations or mistakes on lab equipment or lab procedures. These kinds of errors cause measurements to be either be always high or always low. The last kind of error is gross errors. Gross errors occur when machines or equipment fail completely. However, gross errors usually occur due to a personal mistake. For this experiment, the number of significant figures is very important and depends on the equipment being used. When using the volumetric pipette and burette, the measurements are rounded to the hundredth place while in a graduated cylinder, it is rounded to the tenth place.
A random error is caused by any factor which randomly affects the amount of scatter in the data. An increase in sample size allows averages to be calculated which reduces the effects of these random errors. By removing outliers in the data, the effect of random errors can be further minimised. A large amount of scatter in results indicated low precision and a large number of random errors. Some possible random errors in this experiment may have arisen when measuring the 12mL of milk solution for each test tube; some may have had slightly more and others slightly less than 12mL. Another random error could have occurred when adding 4 drops of methylene blue, some drops may have contained more liquid than others, meaning some test tubes may have contained less methylene blue indicator than
One possible source of experimental error could be not having a solid measurement of magnesium hydroxide nor citric acid. This is because we were told to measure out between 5.6g-5.8g for magnesium hydroxide and 14g-21g for citric acid. If accuracy measures how closely a measured value is to the accepted value and or true value, then accuracy may not have been an aspect that was achieved in this lab. Therefore, not having a solid precise measurement and accurate measurement was another source of experimental error.
I can remember rare occasions as a child when I would wake up for school and there would be pancakes, eggs and bacon on the table and orange juice or Sunny Delight to drink. These exciting occasions, however, were just that: rare. Most days I would bound down the stairs to the toaster loaded with Pop-Tarts. I would usually be disappointed that I couldn't devour a wholesome breakfast, but I later came to understand the convenience of the Pop-Tart. My parents could put pastries in the toaster and continue to get ready for their day without having to worry about too much clean-up. It was during these early days of my education that I really found a love for the sugary, fruit-filled pastries.
Nuts (I eat almonds and raw peanut butter, but most of the nuts are similar in nutrition facts).
Possible sources of error in this experiment include the inaccuracy of measurements, as correct measurements are vital for the experiment.
I love apple fritters. Today I love the idea more than the warm, sticky sweetness. During my college years I knew which donut shops were open at midnight. Eventually the pain in my gut became greater than the pleasure of the apple fritter and I retired those midnight runs to Sam’s donuts in favor of a tart green apple with almond butter. Everything we do eventually settles into providing pleasure and avoiding pain. What makes a personal health plan successful is how we define pleasure and pain.
Hamburgers and Ground Beef Each individual in America has a goal he or she wants to accomplish. Whether it’s to purchase a new car or a huge home, it’s a goal that wants to be reached. However, with the amount of fast food that Americans eat today, they will have a hard time accomplishing these goals because of the obesity or even disease they’ll have from the fast food. One major fast food that we like to eat while on the go is hamburgers. If it’s breakfast we grab a burger, if it’s lunch we grab a burger and even when it’s dinner we grab a burger and might throw in some fire and a huge soda to go with it.
Fruits are much healthier than candy bars. First of all, fruits have fewer calories and less fat than any candy bar. For example, a medium size apple has eig...
The reason I chose this particular area of research is that peanut butter is an extremely popular food choice worldwide as it is affordable and nutritious; and I also love to eat it. However, the number of brands and the choices within the brand range make it complicated for the consumer and myself to choose the most nutritious option. Prior to this research I did not understand the nutritional content of the food I ate.
Our hypothesis for this lab was that the limestone will add mass because it is a sedimentary rock, and weathering and erosion break down a rock. Our data refute our hypothesis because we said it will gain mass when the limestone lost mass. The limestones Initial mass was 3.67, and after we put it in the oven the mass went down too 2.81. The mass went down by 0.86. Also, the graph above shows our data. The red line of the graph was the change in mass after we put it in the oven, and the blue line is the Initial mass. The red line doesn't move that much. After we put the rocks in the oven only one changed in mass. The Limestone changed 0.86 in mass, Quartzite changed 0.00 in mass, and Obsidian changed 0.00 in mass. By that data the oven did not really change the difference in mass. The blue line is our initial mass. Limestone was 3.87, Quartzite was 67.51, and Obsidian was 10.63. In the graph it shows the blue line going up. Our initial mass goes up, but our final mass stayed the same besides the limestone changed by 0.86. In the graph there were two trends. One goes up, and the other one basically stayed the same. The initial mass had a bigger impact because we used 3 rocks, and they were different masses. For the final mass the trend wasn’t that good because two of the final masses stay the same at zero, and the one that changed in mass was only a 0.86
The purpose of this study is to observe the rate of decay of two bananas at different temperatures and determine how temperature affects the rate of decay of bananas. I will perform this study by taking to equally ripe bananas and putting each banana into a plastic bag. Then I will label each bag to make sure when I am making my observations that I don’t mix up the bananas. I will put one of the bags with the banana in it into the fridge and the other bag will be put on my desk in my dorm room. I will record the temperature daily in each location to makes sure that the temperature isn’t changing. I will examine the bananas everyday at the same time and observe any signs of decay. I will take the observations at the same time to make sure there is equal time between each observation so the results aren’t affected. I will