Philosophy and Education Assignment Example | Topics and Well Written Essays - 250 words

Philosophy and Education - Assignment Example Being young kids and curious, excluding them from such participation may instigate hatred and as such; I can include them but protect them in the project by altering the activities they participate in and excluding their data. For example, I will prohibit Janice from the playdrough activity. The study on Math Fluency: Accuracy versus Speed in Preoperational and concrete Operational first and second grade children utilizes a quasi form of experimental design. This is because the study contains aspects of both qualitative and quantitative experiments but lack proper experimental controls that can make the researcher draw firm comparisons. It is easier to generate experimental results for general trends in circumstances where randomization and pre-selection of groups is difficult using a quasi experimental design. From the basis that most quasi experimental designs are integrated with individual case studies; results and figures obtained often affirm the findings and deductions made in a case study and therefore, permit a statistical analysis to take place. Since quasi experimental designs do not need extensive randomization and pre-screening, they cut down on both resources and time required to carry-out an experiment. Such a quasi research design can be improved through ensuring that proper statistical tests are carried out and proper randomization is done. It is necessary to incorporate control factors that might have had effects on experimental results. Since this research design entails an explicitly proven hypothesis: stress processing abilities influence reading development in a second, stress-based, language, with supporting statistical analyses in the form of tables, bar graphs, and other statistical diagrams, it is clearly a true experimental design. Such an experimental design eliminates the possibility of arguments with regard

Gloalization of Spain Term Paper Example | Topics and Well Written Essays - 1500 words

Gloalization of Spain - Term Paper Example This isn’t a reason to turn away from globalization, but it is a reason to be vigilant. This essay will look at the way Spain has become more dependent on other countries through the process of globalization and it will suggest that this has mostly been for the best. Although the exact moment of globalization occurring in Spain is a highly debatable question considering the length of Spains history and its extensive involvement in world affairs, it could be said that 1990s marked the rapid acceleration of the period. Spain decided to go full steam ahead with economic global integration. While other countries were slow to see the positive ramifications of globalization, Spain was not. It saw what it wanted and it struck. After many years of sclerotic economic growth under Franco, Spain was ready to reengage with the world again.1 Of course, with current economic events shaking the world economy, we begin to see some of the potential negative effects of globalization for Spain. The problems point to one of the serious drawbacks of globalization: when you open your economy up to the other economies of the world you can get very rich as long as they do well—but you also become very vulnerable to their problems too. This is something Spain has become concerned about regarding the E.U. in the past, and now with the American economy in shambles, it must again revisit this difficult situation. The global economic crisis has shown that interconnectedness can bring with it negative consequences. While a rising tide lifts all boats, a severe drought makes everyone thirsty. This is a problem that will have to be negotiated on the world stage. Spain has a number of economic problems that result from this, including high unemployment. But in the course of this important debate it is important to remember the benefits that have come with

Alexander The Great Essay Example for Free

Alexander The Great Essay One of the most popular and secular figure in history is Alexander the Great, who was great military leader and king. As you know he was the son of King Philip II, born in Macedonia (356 BC). His father Philip was a great and energetic ruler of his time. Alexander was taught by Aristotle. He learned philosophy, ethics and politics from him. In very early age he stared showing interest in military and showed his brilliance performance in commanding the Macedonians battles in his teens. He helped won the battle of Chaeronea at 18. THE TIME PERIOD He ascended the throne of his father in 336 BC, after the assassination of his father, and took over Thessaly and Thrace. He greatly expanded the kingdom of Greek and Macedonian. He defeated Persian army in 334 BC at the Granicus River. He was destined to rule Asia after he cut the knot in Phrygia 333 BC. He also defeated Persian King Darius III at the battle of Issus 333 BC. Later he expanded his power to Syria and Phoenicia completely rooting off Persians from their port. One of his greatest military achievement was the conquest of Tyre in 332 after which he overcame Egypt. GEOGRAPHY There he founded Alexandria. Then he took control of East Mediterranean coast and again defeated Darius at Gaugamela. Then he conquered Babylon.   In Persia he formed an empire ruled by both Persians and Macedonians. He also took control of Oxus and Jaxartes rivers and founded more of Alexandria cities. He married Persian princess Roxana. He died at the age of 33 after heavy drinking and buried in Alexandria, Egypt. His conquest extended from Thrace to Egypt and from Greece to Indus Valley and expanded Greek and Macedonian Empire. Under his rule, he conquered almost the entire world of his era and expanded the empire of Macedonia and Greek. CLIMATE OF THE AREA The weather was cloudy and occasionally sunny. RELIGIONS OF THE PEOPLE Alexander thought that he had a divine origin. He believed this because of his mother’s conception that he was born from serpent not Philip. This affected much of the Alexander’s life and at some stage of his life he visited Temple of Ammon in Siwah to consult god and to trace his birth. Just like Hercules birth was traced to Zeus, he considered his origin from serpent, Ammon. He wanted to draw a clear connection between him and Hercules, therefore, the coins he minted bear face of Hercules with great resemblance to Alexander. In this way, he stretched the message of his divine origin through out his conquered world. Alexander was also introduced as proskynesis (the one before him others bow) to proof his divinity. The one who is very superior king and all others are inferior to him and should bow in front of him. After the death of Alexander, his successors started to fight for the domination. His empire was then divided in various small empires, namely Egyptian Empire, Seleucos and Macedonian Empire. Most powerful and strongest among these were Egyptian empire. IMPORTANT PEOPLE OF THE TIME Homer was Alexander’s favorite. He used to sleep with a copy of Iliad under his pillow. He learned a lot from Aristotle. When he was 16, he acted as regent of Macedonia. He then thrashed Thracians and founded a new city Alexandropolis. He also went to the Battle to help Philip and saved his life and army.1 He was first taught by Leonidas, who was very strictly disciplined and instilled in him simpleton and abstinent nature. Then he was taught by Lysimahcus. Lysimachus taught Alexander to play lyre, fine arts, music, poetry and drama. At the age of 13 he was taught by Aristotle. THE POLITICS Alexander ascended the throne after the murder of his father and took hold of the troubled kingdom. Alexander Marched towards Athens and Thebes and towards northern side to take hold of the cities who were threatening to break away from Macedonians after Philip’s death. He subdued Athens and Thebes and repelled northern barbarians. Most of the Alexander’s success was due to political and military strength of Philip. Philip’s large contribution to the Macedonian army and acquisition of alliances with Balkans, strengthened his own kingdom and expansion of their empire in Alexander’s era. Philip ascended to the Macedonian throne in 359 BC. At that time, Macedonia was suffering from a defeat and their political and military power was destroying at the hands of Illyrians.2

Effects of Free Trade Agreements on Trade and Growth in US

Effects of Free Trade Agreements on Trade and Growth in US The Effects of Free Trade Agreements on Trade and Growth in American Countries: Evidence from the Gravity Model Approach Trade as a driver of growth and development is a concept that has been addressed from different perspectives or approaches for scholars and policy-makers. However, an integrative path was sealed with the creation of the World Trade Organization as the main tool to promote a more accessible and clear way to commerce between nations and was further strengthened by bilateral and multilateral FTAs, which continue developing and growing. In the current political scenario, the discussion between supporters of globalisation and detractors provides a compelling framework to study the real effects that Free Trade Agreements cause on the economic performance. While the first group affirms that FTAs enhances the markets and therefore, the economic growth and employment, the second group argues that the global market is damaging the small domestic economies. The present paper covers the increasing effects on trade that are expected by countries that engage in Free Trade Agreements, including bilateral or multilateral ones within American countries, in the context of the three central multilateral trade agreements in the continent (NAFTA, MERCOSUR, and The Pacific Alliance) and other relevant bilateral agreements. The main question to be addressed is whether the positive effects predicted by economic theory on trade when countries eliminate fares and other barriers to trade as part of an agreement effectively happen in the current context of the Americas. The hypothesis is that the implementation of Free Trade Agreements has a positive and significant impact on the trade flows between the American countries. Section 2 includes the theoretical framework behind the relation between trade and FTAs, Section 3 presents the model specification, Section 4 shows the estimation of the model and the econometric tests, the limitations of the theoret ical framework and the model specification are discussed in Section 5, and Section 6 concludes. The Gravity Model has its origins on Location Theory, as it was the main model to include the effects of distance on traded quantities. Isard and Peck (1954) acknowledged the importance of considering distance as a variable in trade analysis establishing the ground from which others such as Tinbergen (1962) and Pà ¶yhà ¶nen (1963) would build the Gravity theory to explain trade flows between countries, conducting the first econometric studies based on the gravity equation. The Gravity Model has proven to be extremely successful in ordering the observed variations in economic transactions and movement of factors. It is also distinguished for its representation of economic interaction in a multi-country world, where the distribution of goods and factors is driven by gravity forces that are conditional to the size of economic activities at each location (Anderson, 2010). In this way, trade between countries is positively related to countries sizes and negatively related to distance. Moreover, as a widely used analytical framework, the model can incorporate adjusting variables such as FTA to indicate the existence of Free Trade Agreements between the objective countries (Yang and Martinez-Zarzozo, 2014). Tinbergen (1962) suggests an economically insignificant average treatment effects of FTAs. However, numerous studies, such as Frankel (1997) on MERCOSUR, find a significant positive effect in line with the expected results. These contradictory outcomes emphasise the fragility of the estimation of FTAs treatment effects and are a clear signal that robustness should be tested. One of the central issues to be explored is the exogeneity of FTAs, since the presence of them, if endogenous, can provide seriously biased results. Baier and Bergstrand (2007) provide several important conclusions to be taken into consideration. They observe that using the standard cross-section gravity equation provides a downwards-biased result. Secondly, attributed to this bias, traditional FTAs effects are underestimated by around 75%-85%. Lastly, the authors demonstrate that the best estimates of the effect of FTAs on bilateral trade are achieved from a theoretically framed gravity equation using panel data with bilateral, country and time fixed effects or differenced panel data with country and time effects. As it is suggested by extensive literature, trade flows are better explained by the Gravity Model, which propose the Newtons Gravity concept to explain bilateral trade as an attraction force, influenced positively by the size of the economies involved in trading and negatively with the costs of transaction (Tinbergen, 1962 and PoÃÅ'ˆyhoÃÅ'ˆnen, 1963). As proxy variables of the size of the economy, the model uses GDP and population of both countries; and Distance between the countries as a proxy for transaction costs. Following the Newtons Gravity Equation, the model estimates: Where is the trade flows between a specific country pair, in other words, is the sum of exports from country to country plus exports from country to country . is the gross domestic product in country , is the population of country , is the GDP in country , is the population of country , and is the distance between the capital cities (as major economic centres) of countries and . To avoid spurious effects due to inflation and currency exchange rates, the variables , and are measured in 2010 constant US dollars. Moreover, recent literature has implemented an augmented version of the gravity model to evaluate other variables of interest related to trade flows. In this way, besides to include more time-sections to the analysis, a dummy for implemented FTAs is added to the explanatory variables, taking a value of 1 if there exist a fully in force agreement and 0 otherwise. For the purpose of this paper, an FTA is considered if it establishes 100% free trade, because many cooperation agreements in the Americas consider only certain sectors for free trade, and these are not the focus of this research. Including the dummy variable, transforming the gravity model using Logarithmic function, to accomplish the linearity-in-parameters assumption, and including the time sections, the model to estimate is: However, it is strongly likely that this model has problems of endogeneity and thus, the estimators are biased due to sampling selection and omitted variable bias, how it is suggested by the literature. However, the logic behind this biasedness is different to the literature review. For Baier and Bergstrand (2007), the parameter of interest would have a negative bias because countries will be more interested in implementing an FTA when the benefits of it are greater. Therefore, the authors conclude that a possible omitted variable would be Tariff Barriers. In this scenario, Tariff Barriers are negatively correlated with trade and positively with FTA, generating a negative bias. This is not the case for America. On the contrary, progressive lower barriers and an improving in the diplomatic relationships have finally pushed the creation of Free Trade areas and agreements. That is why, in this case, we suggest that the bias for the sample would be positive, since the possible omitted variables would be lower barriers and good diplomatic relationships, affecting the FTAs and the trade itself positively. To solve this problem, the literature suggests the use of Fixed Effects Panel Data strategy because this model can control for country-specific and invariant-in-time unobservable variables. Therefore, the model to estimate is: Where will be the identifier for the 29 different country-pair units. Since the Fixed Effects model reacts only to variant-in-time variables, the variable Distance is dropped from the model. This estimation allows controlling by characteristics related to the specific country-pair like diplomatic relationships, trade openness, institutions, and so on. However, there could be variables related to unobserved characteristics in time like trade trends and generalised willingness to trade and sign FTAs. For this reason, it is recommended to use time fixed effects to avoid endogeneity, through the next model: Where will be the identifier for the 13 different time sections. Since the scope of this paper is to evaluate the effect of the FTAs on American countries, the three biggest trade agreements in the continent (NAFTA, MERCOSUR, The Pacific Alliance) were taken as a research target, and their members were chosen as the population. The countries included by Trade Agreement are presented in Table 1: Table 1. Multilateral Trade Agreements in America Agreement Country Start Date North American Free Trade Agreement (NAFTA) Canada 01/01/94 Mexico 01/01/94 United States 01/01/94 Southern Common Market (MERCOSUR) Argentina 15/08/91 Bolivia 28/02/97 Brazil 15/08/91 Paraguay 15/08/91 Uruguay 15/08/91 MERCOSUR Chile Chile 01/10/96 The Pacific Alliance Chile 01/02/12 Colombia 01/02/12 Mexico 01/02/12 Peru 01/02/12 Source: Organization of American States (2016) However, if those countries were incorporated without taking into account other Free Trade Agreements between them or third countries, problems of sample selection bias would be created. For this reason, in addition to the mentioned free trade areas, bilateral FTA are considered, according to Table 2: Table 2. Bilateral Trade Agreements in the sample FTA Start Date Bolivia Mexico 07/06/10 Canada Chile 05/12/96 Canada Colombia 21/11/08 Canada Peru 29/05/08 Chile Mexico 01/08/99 Chile Panama 07/03/08 Chile Peru 01/03/09 Mexico Chile 01/08/99 Mexico Uruguay 15/07/04 Panama Canada 01/04/13 Panama Peru 01/05/12 United States Chile 01/01/04 United States Colombia 15/05/12 United States Panama 31/10/12 United States Peru 01/02/09 Source: Organization of American States (2016) As the model considers only one dummy variable, if a country-pair has two agreements in force (bilateral and trade area), it is considered the oldest one. Besides, it is important to point out that Venezuela (suspended member of MERCOSUR) was dropped from the list due to the lack of reliable information about trade flows. The information about bilateral trade flows was obtained from The World Banks World Integrated Trade Solution, and the other variables were constructed using information from the World Development Indicators. The database used to estimate the model has 29 country-pairs (cross-sectional units) and 13 time-sections since 1990 to 2014. The used database of bilateral trade drops 1996, leaving the database with one time-section less. Since it is one time-section of fourteen and according to our investigation, the missing information is not related to an event influencing trade flows and the time section is dropped for the entire observations, we have a low risk of biased estimators. Table 3 contains the descriptive statistics showed by the Statistical Software STATA ® for the variables in levels: Table 3. Descriptive statistics of relevant variables (in levels) Variable | Mean Std. Dev. Min Max | Observations ID overall | 25.45435 19.18174 1 74 | N = 460 between | 19.36072 1 74 | n = 29 within | 0 25.45435 25.45435 | T-bar = 15.8621 | | Exports overall | 4.55E+10 1.22E+11 1.45E+08 6.13E+11 | N = 460 between | 1.01E+11 4.22E+08 4.75E+11 | n = 29 within | 3.63E+10 -1.67E+11 2.48E+11 | T-bar = 15.8621 | | GDP_Exp overall | 1.02E+12 2.25E+12 9.96E+09 1.62E+13 | N = 460 between | 2.40E+12 1.37E+10 1.30E+13 | n = 29 within | 3.60E+11 -1.94E+12 4.21E+12 | T-bar = 15.8621 | | Pop~Exp overall | 6.71E+07 7.28E+07 2738125 3.19E+08 | N = 460 between | 7.16E+07 3324953 2.86E+08 | n = 29 within | 8255115 3.64E+07 9.97E+07 | T-bar = 15.8621 | | GDP_Imp overall | 6.78E+12 6.55E+12 9.96E+09 1.62E+13 | N = 460 between | 6.28E+12 1.61E+10 1.38E+13 | n = 29 within | 1.50E+12 2.71E+12 1.00E+13 | T-bar = 15.8621 | | Pop~Imp overall | 1.68E+08 1.31E+08 3201604 3.19E+08 | N = 460 between | 1.31E+08 3310046 2.95E+08 | n = 29 within | 1.42E+07 1.31E+08 2.00E+08 | T-bar = 15.8621 | | FTA overall | 0.5043478 0.5005254 0 1 | N = 460 between | 0.4360526 0 1 | n = 29 within | 0.2546286 -0.453985 1.393237 | T-bar = 15.8621 | | Distance overall | 3690.712 2529.406 213.02 8483.39 | N = 460 between | 2533.405 213.02 8483.39 | n = 29 within | 1.55E-12 3690.712 3690.712 | T-bar = 15.8621 However, since the estimations are calculated using a logarithmic transformation of the continuous variables, the descriptive statistics of the variables in natural logarithm are presented in Table 4: Table 4. Descriptive statistics of relevant variables (in logarithm) Variable | Mean Std. Dev. Min Max | Observations FTA overall | 0.5043478 0.5005254 0 1 | N = 460 between | 0.4360526 0 1 | n = 29 within | 0.2546286 -0.4539855 1.393237 | T-bar = 15.8621 | | lexports overall | 2.25E+01 1.84E+00 1.88E+01 27.14178 | N = 460 between | 1.64E+00 1.98E+01 26.85607 | n = 29 within | 5.17E-01 2.10E+01 23.84729 | T-bar = 15.8621 | | lGDP_ex overall | 2.65E+01 1.66E+00 2.30E+01 30.41464 | N = 460 between | 1.69E+00 2.33E+01 30.18564 | n = 29 within | 2.28E-01 2.58E+01 27.04886 | T-bar = 15.8621 | | lGDP_im overall | 2.77E+01 2.795514 2.30E+01 30.41464 | N = 460 between | 2.719438 2.35E+01 30.25019 | n = 29 within | 1.94E-01 2.70E+01 28.17505 | T-bar = 15.8621 | | lPop_ex overall | 1.75E+01 1.11E+00 1.48E+01 19.58041 | N = 460 between | 1.12E+00 1.50E+01 19.47142 | n = 29 within | 8.70E-02 1.72E+01 17.64414 | T-bar = 15.8621 | | lPop_im overall | 1.80E+01 1.821994 1.50E+01 19.58041 | N = 460 between | 1.826536 1.50E+01 19.50204 | n = 29 within | 8.05E-02 1.78E+01 18.19405 | T-bar = 15.8621 | | ldista~e overall | 7.89E+00 9.17E-01 5.36E+00 9.045865 | N = 460 between | 9.10E-01 5.36E+00 9.045865 | n = 29 within | 0.00E+00 7.89E+00 7.891049 | T-bar = 15.8621 Although using pooled OLS with the database will generate problems of endogeneity discussed further below, OLS estimation is made to have the first approach to the gravity model. Table 5 shows the obtained results: Table 5. Gravity Model estimated by OLS lexports | Coef. Std. Err. t P>|t| [95% Conf. Interval] lGDP_exp | 0.6340649 0.0394767 16.06 0 0.5564848 0.7116451 lGDP_imp | 0.4512511 0.0464715 9.71 0 0.3599247 0.5425775 lPop_exp | 0.2196251 0.0606458 3.62 0 0.1004432 0.3388071 lPop_imp | 0.5049373 0.0726212 6.95 0 0.362221 0.6476536 FTA | 0.5136195 0.0689928 7.44 0 0.3780338 0.6492052 ldistance | -0.9256142 0.0407673 -22.7 0 -1.005731 -0.8454978 _cons | -12.68833 0.7146799 -17.75 0 -14.09283 -11.28383 With a , the model behaves according to the literature and all variables are statistically significant using any level of significance. The variables measuring the mass of the economies are positive and distance is negative. Additionally, the variable of interest FTA is positive and statistically relevant, showing tha

Betrayal in McEwans Atonement Essay -- Literary Analysis

In McEwan’s Atonement ventures into the lives of the Tallis sisters and the complexities that naivety and selfishness can inflict. Briony Tallis’ perjury against Robbie Turner, in her cousin Lola’s criminal rape case, disrupts the Tallis family dynamic and the budding romance between Cecelia Tallis and Robbie. Briony’s maturation and realization of her wrongdoing implores her to become a nurse during WWII. In Atonement, McEwan depicts a family in turmoil over the lies of young Briony during World War II. The imagery and symbolism portray Briony’s characterization through her attempts to serve penance for her betrayal with symbolism and imagery. Briony’s limited point of view effects the tone of the novel through an unreliable eyewitness account of what she witnessed and the recognition of her mistakes. Atonement’s symbolism of innocence shows Briony’s youthful naà ¯vetà © and her blameless intentions. The symbolism of lost innocence not only affects Briony, but Cecilia and Robbie as well. Robbie and Cecilia venture into the world of adult sexuality together, but are interrupted by Briony’s curiosity. Witness to the debauchery at hand, Briony skews her testimony to the police in regards to her encounter of Lola and her rapist at the temple, â€Å"Events she herself witnessed foretold her cousins calamity. If only she, Briony, had been less innocent, less stupid. Now she saw, the affair was too consistent, too symmetrical to be anything other than what she said it was. She blamed herself for her childish assumption that Robbie would limit his attentions to Cecilia. What was she thinking of? He was a maniac after all.† (158) Briony thought of the obscene note written to Cecelia as a warning to what Robbie was capable of, although the note w... ...Rpt. In Contemporary Literary Criticism. Ed. Jeffrey W. Hunter. Vol. 269. Detroit: Gale, 2009.Literature Resource Center. Web. 09 Dec. 2011. Mathews, Peter. "The Impression of a Deeper Darkness: Ian McEwan's Atonement." English Studies in Canada 32.1 (2006): 147+. Literature Resource Center. Web. 3 Jan. 2012. McEwan, Ian. Atonement. New York: Anchor, 2003. Print. Finney, Brian. "Briony's Stand Against Oblivion: The Making of Fiction in Ian McEwan's Atonement." Journal of Modern Literature 27.3 (Winter 2004): 68-82. Rpt. In Contemporary Literary Criticism. Ed. Jeffrey W. Hunter. Vol. 269. Detroit: Gale, 2009. Literature Resource Center. Web. 2 Jan. 2012. Shone, Tom. "White Lies: Ian McEwan's Novel Chronicles the Disintegration of an English Family's Idyllic Life." The New York Times Book Review 10 Mar. 2002: 8+. Literature Resource Center. Web. 5 Jan. 2012.

How to get a Job in the US :: Resume, Cover Letter

In the United States, it is very difficult to acquire an occupation with so many people struggling and striving to get a position that only one applicant can have. A course of action one may take to place himself above others in the eyes of the employers is to plan and submit an outstanding resume. A resume is a professional approach to provide employers with written evidence of one’s qualifications and skills. Resumes are required for professional, technical, administrative, clerical, sales, secretarial, managerial, and many other jobs (â€Å"Resume Writing† 1). It is essential to have an impressive resume for one to attain a decent job and earn a reasonable salary. There are three critical steps to take, in order to complete a successful resume such as gathering information, creating a cover letter, and creating a resume. The first step in this fulfilling task is gathering the information that will be applied in the cover letter and resume. The main components of information that must be compiled are as the following: past awards, recognitions, honors, job history, clubs, and college or high school transcripts. Another crucial component of information that needs to be acquired are the references. References can be anyone from past teachers to family friends to family doctors. References are important because they are the people that will tell what kind of person one is to the employer. One must gather all the information one wants to insert in his resume. Also one must begin a list of appropriate skills for whatever job he is applying for. Some desirable skills are basic computer skills, communication skills, and organizational skills. After compiling all of this information one is ready to submit the information into the cover letter and or resume. Next one must create a cover letter to showcase his top qualities in a single page (â€Å"Savvy Cover Letter† 1). The cover letter basically summarizes an applicant’s abilities (â€Å"Resume Writer† 1). To create the cover letter one must get a template to show the format of the cover letter, so one can implement his qualifications in it and customize it himself. One can also take a cookie-cutter approach to it and just take the easy way out (â€Å"Savvy Cover Letter† 1). One must keep in mind that he is trying to convince the employer to be interested in him enough to read his resume and eventually call him in for an interview.

Identifying Macromolecules in Common Foods Essay

Abstract: We tested five common food items to determine which macromolecules were present. We tested for the macromolecules of simple and complex carbohydrates (sugars and starch), lipids, and proteins. The foods tested were coconut milk, karo syrup, potato chips, peanut butter, and banana baby food. We hypothesized that coconut milk would contain all four types of macromolecules, karo syrup would only contain simple sugars which are monosaccharides and/or disaccharides, potato chips would contain starches and fats, peanut butter would contain sugars, fats, and proteins, and banana baby food would consist of sugars and starch. Each macromolecule test consisted of five test tubes of the food item individually diluted into solutions for reacting each with Benedict’s reagent to show the presence of sugar, IK2I for starch presence, and Buiret’s reagent for protein presence. A simple paper test was used evaluting lipid existence for each food. Our results confirmed our estimations of the foods’ compounds. The testing results verified that coconut milk contained all four types of macromolecules, karo syrup contain only simple sugars, potato chips were starches and fats, peanut butter contained sugars, fats, and proteins, and banana baby food consisted of sugars and starches. Introduction: Identifying macromolecules in the foods we eat is essential in comprising a healthy well-rounded diet ensuring our nutritional needs for cellular processes in the human body. The largest biological molecules are known as carbohydrates, lipids, and proteins. Carbohydrates are compounds of monosaccharides, disaccharides, and polysaccharides known as sugars and starches. Lipids, known as fats, are storage molecules in animals and plants. Proteins bind to other molecules performing key roles in DNA and RNA functions. Five different food items were tested for the presence of specific macromolecules identified as sugars, starch, lipids, and proteins. The food items were coconut milk, karo syrup, potato chips, peanut butter, and banana baby food. We used chemical indicators and brown paper to detect the presence of different macromolecules in various solutions made from each food sample. If sugars were present in a food, then the Benedict’s reagent and heat would turn the solution orange and precipitate will form. If starch was present, then the iodine potassium iodide would turn the solution dark purple or brown and form a precipitate. If lipids were present in a food, then the brown paper it was rubbed onto would form a transparent area. If a food contains protein, then the Buiret’s reagent would turn the solution violet or purple in color. Our observations of the changes to the solutions in color and consistency indicated the presence of each different macromolecule according to the food item (see Table 1, Chart 1). We predicted that coconut milk would contain sugars, starch, lipids and proteins; karo syrup would only be a simple sugar; potato chips were made of starch and lipids; peanut butter would contain sugars, lipids, and proteins; and banana baby food would only contain sugars and starch. Materials and Methods: We tested five food items for sugars, starch, lipids, and protein. The items tested were cocunut milk, karo syrup, potato chips, peanut butter, and banana baby food. All of these food items were thick in consistence. Also, several of the foods had heavy coloring which would make some of the tests difficult to visually measure. Solutions were made of each food item. Our lab professor dilute the foods with water to form solutions for us to test. According to our lab manual, The Pearson Custom Library for the Biological Sciences, chapter Macromolecules, the testing methods are as follows (reference II). Before any testing chemicals or testing procedures were performed, the intial states and colors of the food solutions were as follows: the negative control water was clear and colorless; coconut milk was opaque and white; karo syrup solution was completely transparent and colorless; potato chip solution was cloud and slightly yellow; peanut butter solution was cloudy and slightly beige; banana baby food solution was cloudy and slightly yellowish beige. Simple Carbohydrates (Sugar) Testing: Using Benedict’s testing on our food items, we tested for simple sugars. Six clean test tubes were labeled individually with each testing food item plus one negative control test tube. Solutions of each food item in the quantity of one full dropperful was added to each labeled test tube and one full dropperful of water was added to the control tube. Then, each test tube received one full dropperful of Benedict’s reagent and was gently shaken to mix the solution. Each test tube was then placed in a hot water bath in a beaker of water on a hot plate for approximately 2 minutes. After approximately 2 minutes, the test tubes were removed from the water and placed into the test tube rack for us to observe any changes to the solutions. The resulting states and colors of the test tubes were as follows: The negative control water was clear and blue in color; coconut milk was opaque with a dark orange precipitate in the bottom and orange through the rest of its solution; karo syrup was opaque with a dark orange precipitate in the bottom and orange throughout its solution; potato chips solution remained cloudy with no precipitate and was blue in solution; peanut butter solution was opaque with a brown precipitate in the bottom and brown through its solution; and the banana baby food solution was opaque, dark brown in color and formed a dark brown precipitate in the bottom of the test tube. Complex Carbohydrates (Starch) Testing: Iodine potassium iodide (IK2I) was used to test for polysaccarides. Six clean test tubes were labeled and placed in a test tube rack. Five of the test tubes were individually labeled with each of our five food items and one test tube was labeled â€Å"control†. The control test tube one full dropperful of water, the other five test tubes received their identified food item in the quantity of one full dropperful. Then, one droplet of the IK2I reagent was added to each of the six test tubes and were mixed well. The resulting states and colors of the test tubes were as follows: The negative control water was clear and yellow amber in color; coconut milk formed a dark brown precipitate and an opaque solution color of violet-beige; karo syrup remained translucent and deep amber in color; potato chips solution formed a dark purple precipitate with an opaque solution color of purple; peanut butter solution remained cloudy and yellow in color; and the banana baby food solution formed a purple brown precipitate and an opaque solution of pinkish beige. Lipid Testing: We performed a non-coated paper test on our chosen food items to identify the presence of lipids. Six squares of non-coated brown paper were obtained and labeled with the five food items to be tested and one control paper labeled â€Å"water†. The control paper received a droplet of water rubbed into the paper. Each of the five separate foods were added and rubbed onto the center of each of their identified brown paper. The papers were set aside for 30 minutes to absorb the contents and dry. After the 30 minutes, each paper was held towards the overhead light. The coconut milk, potato chips, and peanut butter papers all showed translucent areas where the food was applied. The Karo syrup and the banana baby food dried completely and showed no translucent areas, being completely opaque in their paper centers. Protein Testing: The Biuret’s test was performed on each of our five food items to identify the presence of protein in the foods. Six clean test tubes were labeled and placed in a test tube rack. Five of the test tubes were individually labeled with each of our five food items and one test tube was labeled â€Å"control†. The control test tube had one full dropperful of water, the other five test tubes received their identified food item in the quantity of one full dropperful. Then we added one full dropperful of of buiret’s reagent to each of the test tubes, agitated the tubes to mix thoroughly, and observed any changes. The resulting states and colors of the test tubes were as follows: The negative control water was clear and light blue in color; coconut milk was opaque and violet-brown; karo syrup remained translucent with slightly blue solution color; potato chips solution remained cloudy and turned more slightly grayish in color; peanut butter solution was opaque and became pinkish in color; and the banana baby food solution was opaque and turned brownish slightly green color. Results: Coconut milk tested positive for sugar indicated by a dark orange precipitate forming and an orange solution. Coconut milk tested positive for starch as it formed a brown precipitate with a beige colored solution. Coconut milk tested positive for lipids as the paper developed transparency. Coconut milk tested positive for proteins by resulting in an opaque, violet-brown solution. Karo syrup tested positive for sugar by exhibiting a dark orange precipitate and an orange solution. Karo syrup tested negative for starch, lipids, and proteins as there was no resulting changes. Potato chips tested positive for starch by producing a dark purple precipitate and a purple solution. Potato chips tested positive for lipids forming transparency on the testing paper. Potato chips tested negative for sugars and proteins indicated by no trend changes to their solutions. Peanut butter tested positive for sugar forming a brown precipitate and a brown solution. Peanut butter tested positive for lipids by developing transparency on the testing paper. Peanut butter tested positive for protein by resulting in a pinkish beige solution. Peanut butter tested negative for starch as the solutuion remained yellow in color. The banana baby food tested positive for sugar resulting in a dark brown precipitate and dark brown solution. Banana baby food tested positive for starch by resulting a brown precipitate and a pink-beige solution. Banana baby food tested negative for lipids and proteins observing no trending changes. Discussion: Our results supported our hypotheses and predictions developed from our previous exposure to these foods with knowledge of taste, texture and common dietary information. Coconut milk contained sugars, starch, lipids and proteins; karo syrup contained simple sugars; potato chips contain starch and lipids; peanut butter contained sugars, lipids, and proteins; and banana baby food contained sugars and starch (see Table 1 and Chart 1). According to Functional Properties of Food Macromolecules, Second Edition (reference IV), Benedict’s reagent is a clear, blue liquid used to test for simple sugars such as monosaccharides and disaccharides. When Benedict’s reagent and simple carbohydrates are heated together, the solution will turn color to orange red. This color change is caused by the copper (II) ions in the reagent are reduced to copper (I) ions. Sometimes a reddish precipitate forms in the base of the test tube. Information provided by Science and Health Education Partnership, SEP Lessons by University of California San Francisco (reference III) details that Buiret’s reagent is a clear, blue liquid that when in the presence of proteins will change to a purple or even pink color when the copper atoms of the reagent react with proteins or polypeptide chains. Iodine solution or Lugol’s reagent changes from an amber color to dark purple of even black. Due to the original coloring of the foods, the resulting color changes and formed precipitates were adjusted according to the mixture of the reacting coloring. For examples, the peanut butter and banana baby food both were an original brown color so as they reacted with Benedict’s reagent and were heated they resulted in a darker brown color as the common orange reacting color mixed with their original brown coloring. These brown colorings were taken into consideration as we reviewed the ending reactions to justify a positive or negative identification. References Cited: I. Molecular Biology Initiative. Georgia Southern University, GA. http://cosm.georgiasouthern.edu/biology/mbi/activities/Macromolecules%20in%20food/Macromolecules%20in%20food%20activity.pdf. Accessed February 11, 2013. II. Pearson Learning Solutions. â€Å"Macromolecules,† in The Pearson Custom Library for the Biological Sciences. Boston, MA: Pearson Learning Solutions, 2012, pp. 69-87. III. Science and Health Education Partnership, SEP Lessons. University of California San Francisco. http://seplessons.ucsf.edu/node/362. Accessed February 11, 2013. IV. S.E. Hill, D.A. Ledward, and J.R. Mitchell. Functional Properties of Food Macromolecules, Second Edition. Gaithersburg, MD: Aspen Publishing, 1998.