Biology Eei Enzymes - 6364 Words

YEAR 11 BIOLOGY EEI YEAR 11 BIOLOGY EEI JOSHUA CURSON JOSHUA CURSON ANIMAL PHYSIOLOGY- ENZYMES ANIMAL PHYSIOLOGY- ENZYMES ------------------------------------------------- THE ENZYME IS MIGHTIER THAN THE SWORD Effects of Temperature on Amylase Activity ABSTRACT: The aim of this EEI was to test the effects of temperature on the activity of the enzyme Amylase. Solutions of starch and amylase were held at selected temperatures by various methods of temperature control. Once the solutions reached and maintained the desired temperature they were combined. Samples at timed intervals were then taken and reacted with a reagent to determine the effect the selected temperatures had on the reaction rate of enzyme and†¦show more content†¦A constant temperature water bath will be needed to maintain temperature. All enzymes and starch solutions will be maintained in the optimum pH so as to ensure a fair test (REFER TO FIG-32). The following is an EEI designed to test the effects of temperature on the activity of the enzyme Amylase. This experiment on enzymes was done to help convey how environmental factors affect the activity of an enzyme. The experiment will revolve around changing one variable (temperature), measuring one variable (color of the samples in the spot plate/reaction rate/time) and keeping everything else the same (optimum pH/volume of reactants and the reagent). To test the effects of temperature on the activity of amylase, solutions of the enzyme and starch will be reacted with each other at controlled temperatures 70oC, 50oC, 37oC, room temperature and 4oC and below. To find out what effect these temperatures have on the activity of the enzyme, a sample of the resulting solution will be taken at allocated times and be placed onto a spot plate where a test for starch will be done by adding iodine reagent. The relative enzyme activity in the spot plate will be assessed as follows: Iodine test for starch | Amount of starch remaining | Enzyme activity level | Yellow/gold | NONE | NORMAL 5 | Light purple/silver/grey | SOME, | MODERATE 4 | Tan/lightShow MoreRelatedHow Heat Affects Lipase1180 Words   |  5 PagesFactors Affecting Enzyme Action ------------------------------------------------- Term 1 Biology Nicole Goosen Table of Contents Introduction: 3 Materials: 3 Method: 4 Risk assignment: 4 Risk: 4 Personal Protective Equipment: 4 Results: 5 Discussion: 5 Conclusion: 6 Introduction: How is the human body able to digest the food that you eat? How quickly your body digests your food? This is because the human body contains enzymes that are the biological substance, a.k.a proteinsRead MoreAn Experimental Investigation On A Bacterial Outbreak3369 Words   |  14 PagesThis is an Extended Experimental Investigation on a bacterial outbreak in a workplace. The key ideas and concept, is based around health and disease with the prevention of bacteria being the key purpose. The intention of the EEI is to develop a scenario which can be modified to demonstrate and test different variables, these variables include, water, soap, anti-bacterial soap and Dettol’s effect on the chosen bacterial outbreak. The chosen bacteria is, Staphylococcus Epidermidis and its effect inRead MoreWine Analysis of Fining Agents Chemistry8372 Words   |  34 Pages16- Graph5. Turbidity over time 9.17- Graph6. Electrical conductivity over time 9.0- Discussion 10.0- Conclusion 11.0- Appendices 12.0- References 13.0- Special Acknowledgments 1.0-Abstract: The construction of this EEI was conducted in accordance to the term 2 context (Wine: an artful process). This report is intended to present the experimental and analytical aspects of wine chemistry with focus on fining agents. By testing these fining agents on wine samples, their

Comparing and Contrasting Sophocles Antigone and...

The tragedies of Antigone and Othello were written with great depth and are structured in such a way that both characters are victims, in spite of their crimes. Antigone and Othello are tragedy plays created by using many techniques to create the feelings of fear and pity. There are differences and similarities in characters, action, and themes between Antigone and Othello. First, the major characters in both of the plays are suffering through great pain and end up with death. The drama Antigone which is written by Sophocles, tells the story of Antigone. Antigone is a tragic heroine who doesn’t have the power to challenge the authority of the king; she has to obey the rules. However, she shows her strong will and voices her opinions†¦show more content†¦At the beginning of the drama, Desdemona wants to marry Othello; even through her father doesn’t want her to. She makes the choice by herself in Act I, scene iii in an act of willfulness. However, in the final s cene, when she is murdered, Emilia ask her, â€Å"O, who hath done this deed?† Desdemona says , â€Å"Nobody, I myself. Farewell. Commend me to my kind lord. O, farewell† (V.ii.133–134). Desdenona takes responsibility of her death because she wants to protect her husband. She begins the play as a independent and thoughtful person, but she must struggle against all odds to make Othello believe that she is not too independent. Desdemona is a symbol of innocence and helplessness. However in the beginning of the play, she seems to be mature and quite insightful of events around her. Iago often tells Othello that she is unfaithful. It seems that she refuses to accept what Iago is doing. She has a tendency to be sympathetic towards other peoples situations, like Cassio. This also further inspired Othellos jealousy when Iago pointed out that Cassio and Desdemona were speaking in private. She often pays attention to other people’s thoughts, yet remains distrustful if they differ from her own. She has a loyalty to her husband in all aspects of life, Similarities between Antigone and Othello arise in the fact of how the tragedies end and in both stories, we can feel the

The Prevalence of Breast Cancer among Women - Myassignmenthelp.Com

Question: Discuss about theThe Prevalence of Breast Cancer among Women. Answer: Research Design Plan Elements Description and explanation Evaluation of potential understanding Research question and the main elements 1. What is the condition and experience of persons living with breast cancer? 2. What is the experience of children brought up mothers diagnosed with breast cancer? 3. What are measures in place to deal with rising breast cancer cases? The research questions shall assist in understanding the prevalence of breast cancers cases: Emerging issues Literature review Similar to all other types of cancer, breast cancer is one of the deadly disease and one which is killing almost one per hour globally (Thomson, 2014). According to research carried out, United Kingdom leads in the number of women who are tested positive for breast cancer; the study showed that most of those women who are diagnosed with this disease are female above 50 years of age (Holloway, 2016). Nevertheless, younger women were also found to have breast cancer in particular individual cases. Almost one out of ten women are diagnosed with breast cancer during their entire lifetime which sends an alarm to the reason for the study (Taylor, 2015). Doctors together with the international humanitarian Organizations brag of milestones in reducing cancer cases in their countries as well as globally. However, the ratio of breast cancer diagnosis is quite high. Although there is a great chance for women who are tested early to be treated, it remains to be a deadly disease (Kasimir-Bauer, e t al, 2012). According to research conducted by the University of Michigan students, it showed that any woman no matter the food intake or the number of activities that do per day are at a high chance of testing positive for breast cancer (Ed,2012). Hence it is imperative for every woman to check their breast regularly for any symptoms and where applicable seek medical attention from their GP. Although it is not sure of the cause, scholars attribute, age, previous benign breast lump, obese and excessive alcohol use as some of the causes of the deadly disease(Sullivan-Bolyai, 2014). From the brief literature review, it is clear that there have not been numerous researchers who have researched or bothered to test the hypothesis on the prevalence of breast cancer across the continents. Hence this research lies at the best opportunity and position to fill in the gap between the diagnosis of disease on patients, the life of the patients as well as the cause for the increase in the cases of breast cancer as compared to the previous years. Research methodology Research Design: Descriptive research design. The study shall apply descriptive research design. As per Gay, descriptive analysis is the process of collecting data to test the hypothesis or to answer questions regarding current status of elements in the study (Matthews, 2014). The design is the best for the study since it shall report on the first-hand interaction of mothers diagnosed with breast cancer. The methodology and design are best for the study since it will report the engagements of women diagnosed with breast cancer while in hospitals as well as at home. The methodology shall bring out information on their human as well as physical environments, in turn, provide valuable information regarding breast cancer and patients which will be used to be able to ascertain the reason for escalated cases of cases of breast cancer(Sullivan-Bolyai, 2014). With this methodology, the real information regarding the patients and their subjects of study which include nurses shall help inquire in more detailed form. Study areas: The areas of this study shall entail, hospitals especially the cancer centers, homes of patients with cancer and regions identified as cancer prevalent. Study population: the target population of this study shall comprise of patients diagnosed with breast cancer, children of mothers diagnosed with breast cancer, nurses handling these patients and oncologists who have expertise in breast cancer (Neuman, 2014). The target population shall also include nutritionist who will offer expertise on causes of breast cancer. Descriptive research design and methodology is one of the best design on the study since it will assist in the collection of data which is from the primary sources (Kasimir-Bauer, 2012). The methodology shall help me to gain the life experience of the mothers living with breast cancer and their children to know when it was diagnosed and treatment plan. The research methodology shall also inquire on lives of nurses treating these patients and their efficiency, hence assist in investigating if there is civic education. Through the method, we shall also inquire more from oncologists. Through the inquiries from key informants, I will be able to gain more knowledge on the reasons or causes that are propelling the prevalence of breast cancer in the world across the continents. Key informants shall also assist to understand the gap lying between so many patients contracting breast cancer despite the World Health Organization efforts for civic education. Is it their failure as the health department or other agencies? Data and collection method/strategies with consideration of ethics and cultural competence Different data collection methods shall be used at various stages of the nursing study. The entire study shall triangulate data collection methods where possible to be able to acquire reliable data. These data methods shall utmost promote ethical consideration as well as cultural differences present in our diverse study population (Sohoni, 2014). Survey method: it shall be the primary method of data collection. There shall be questionnaire issued to respondents. The study shall make use of both the closed and open ended questionnaire on all the respondents involved. The questionnaire shall be of use in generation of data that will be analyzed using qualitative and quantitative to give standardized outcomes which will be statically tabulated (Englander, 2012). Focus group discussions: This Is one type of data collection, which majors on group dynamics and gives the opportunity to the small group of respondents who are guided by a skilled moderator, who assist the team into deep levels of inquiry and issues surrounding the topic of research (Jayasekara, 2012). Note taking techniques, and the tape recording shall accompany this method to gather more information (Panneerselvam, 2014). It is one of the most important ways since it prompts discussion in the topic of debate, which in our case is breast cancer. Key informants: this is the data collection method that constitutes of the oral source of information from experts. The key informants are repositories of knowledge from which the researchers get expertise knowledge (Neuman, 2014). In this research, the key sources will include oncologists, nurses, and nutritionists. Based on their training and professional experience, the principal sources shall provide information both quantitative and qualitative regarding the problem of breast cancer and emerging issues. Structured Observation method: This will also be used in the research to observe and note the nonverbal communication of the respondents during the interviews to ensure that clear understanding of the primary objective is attained(Matthews, 2014). It will also be important to record on the physical environment of the hospitals where patients are placed. Secondary data: This is where I will use articles and journals that have been written and published regarding breast cancer and those relating to my topic of interest. All the data collection methods are the most important and noble methods to use in this research and ones that will uphold the ethics of research; confidentiality and plagiarism of the secondary data. In the event where I approach a patient, I will introduce the purpose of the research as well as seek authority from the relevant to carry out the research. Analysis and interpretation of data The data that will be collected during this study shall be analyzed in both qualitative and quantitative methods. The qualitative analysis shall deal in deriving explanations as well as interpret the findings entirely basing our comments on the descriptions of the entire engagement of patients at home and those at home and their interaction with their family. The quantitative analysis shall include deriving of the statistical descriptions as well as the interpretation of data using various descriptive statistics (Grbich, 2012). The numerated, as well as the Likert scale questionnaire data, shall be analyzed and document using the SPSS, this is to be done by a social scientist to reduce chances of short falls (Gelman, et al, 2014). The findings generated from the data which will be analyzed using the SPSS shall be presented using, pie charts, percentage tables as well as frequency tables. The qualitative analysis shall be important in the search for content and themes in the qualitati ve data generated from, the key informant interviews, biographic and as well as focus group discussions (Sohoni, 2014). The results of this qualitative data shall be of use to explain the patterns that are emerging as far as breast cancer is concerned from the descriptive statistics. Limitations and Implementation of the research in practice There are plenty of limitations that I will be faced with in the implementation as well as the research of the proposal: First and foremost I expect resistance from the oncologist to offer best regarding their failures to assist the patients (Taylor, et al, 2015). The language barrier is also a challenge I expect. When it comes to implementation of the research, I expect resistance to change from the medical practitioners in service. For instance, FGD has not been used in the medical setup and having sourced out plenty of data from the settings; most PR actioners are more likely to down the research. I also lack the chance to make policies regarding the recommendations of my research. References: Englander, M. (2012). The interview: Data collection in descriptive phenomenological human scientific research. Journal of Phenomenological Psychology, 43(1), 13-35. Gelman, A. C. (2014). Bayesian data analysis . (Vol. 2). Boca Raton, FL: CRC press. Grbich, C. (2012). Qualitative data analysis: An introduction. sage. Holloway, I. . (2016). Qualitative research in nursing and healthcare. John Wiley Sons. Jayasekara, R. S. (2012). Focus groups in nursing research: methodological perspectives. Nursing outlook, 60(6), 411-416. Kasimir-Bauer, S. H. (2012). Expression of stem cell and epithelial-mesenchymal transition markers in primary breast cancer patients with circulating tumor cells. . Breast Cancer Research, 14(1), R15. Matthews, B. . (2014). Research methods. Pearson Higher Ed. Neuman, W. L. (2014). Basics of social research. Canada: Pearson. Panneerselvam, R. (2014). Research methodology. . PHI Learning Pvt. Ltd.. Screening., I. U. (2012). The benefits and harms of breast cancer screening: an independent review. The Lancet, 380(9855), 1778-1786. Sohoni, M. (2014). Data Analysis and Interpretation. Sullivan-Bolyai, S. B. (2014). Data Collection Methods. Springer Netherlands: In Encyclopedia of Quality of Life and Well-Being Research . Taylor, S. J. (2015). Introduction to qualitative research methods: A guidebook and resource. John Wiley Sons. Thomson, R. E. (2014). Data analysis methods in physical oceanography. Newnes.

Maths Statistic Coursework Essay Example

Maths Statistic Coursework Essay I have been given the task of finding what affects the price of a used car, using a spreadsheet given to me displaying data on a hundred cars with data on about each car. The data on the cars were: (See Spreadsheet 1)Make Model Price When NewUsed Price Age ColourEngine Size Fuel Type MPGMileage Service OwnersLength of MOT Tax (Months left) Insurance GroupDoors (Amount) Style Central LockingSeats Gearbox Air ConditioningAirbagsImmediately from looking at those categories I omitted colour, fuel, service, doors, style, central locking, seats, gearbox, air conditioning and airbags. I omitted this data because it is of a low range of contains words, these would be hard to show on graphs and would show me little evidence of what affects a used car price.E.g. Colour: Cannot produce a scatter graph as it uses words.Seats: Has a range of 2-5 and would produce poor scatter graphs and would be hard to find a direct relationship on.Then from the remaining categories I picked age, insurance group , MPG, mileage and of course used price, as this is what I was investigating. It then dawned one me that I could use the depreciation price, the price when I took the used price away from the new, this perhaps could be a more accurate look at the data as some cars depreciate quicker than others. Looking further into that work I decided against it as it would take longer and time was of the essence, but this was perhaps an extension that could be added on at the end.Reasons Why* Age: Has a large range and would be interesting to see what sort of relationship there is* Insurance Group: Again a wide range.* MPG: Grouped data could be used on cumulative frequency graph and has quite a large range.* Mileage: Huge range and a definite effecter of used price but would be interesting to exactly how much.SampleI was given 100 cars but to investigate this would be very time consuming so I would have to bring that number down. In the end I chose to do a 40 car sample as it is a round number, l ower than 100 but still big enough to display a fair representation of the data supplied.Sampling MethodNow Ive decided how big I need my sample, I know have to decide how I will sample. There are two main methods random or stratified, eventually I want to try both but for now I will use a random sample. To do this I will use the random number function on my calculator.I press the random number button and a 3 decimal place number is displayed, I then picked the first 2 numbers and used this as my sampling method. If a number was repeated I ignored it and chose again.EG.Random produced number 0.311 so I chose car number 31Random produced number 0.981 so I chose car number 91Using this sampling method I chose my first group of cars. They ended up being numbers.1 2 4 5 7 8 15 16 17 18 21 22 24 26 27 31 32 35 37 38 44 51 53 63 65 67 68 70 71 73 76 77 83 86 91 95 96 97 98 98From these car numbers I made a table with all the data on the cars above thats I needed such as used price, MPG an d mileage. (See Spreadsheet 2)From this data I complied for scatter graphs on:* Age against used price* MPG against used price* Mileage against used price* Insurance group against used priceI used scatter graphs as they will display relationships between the data, which is why used price is in everyone. A scatter graph will also give me the ability to put a line of best fit in giving me the ability to predict future data.Predictions* For age I believe there will be a very strong negative correlation as the older the car gets the lower the price.* For MPG I believe there will be a weak positive correlation as the higher the MPG the higher the price but I believe it doesnt affect it that much.* For mileage I believe there will be a very strong negative correlation as the mileage increases the price will decrease.* For insurance group I believe there will be a weak negative correlation as the higher the insurance group the price will decrease but not by much.As you can see from my pred ictions I believe that mileage will affect used price the most while insurance group will affect it the least from the ones I chose.See scatter graphs 1, 2, 3 and 4.Conclusions of Random Sampling.As you can see some of my predictions were right while others werent.* Age was a big effecter of price and had quite a strong negative correlation as I predicted.* MPG again had a very strong negative correlation showing it did affect price a lot, which I predicted wrongly.* Mileage had quite a strong negative correlation but not very strong as I said. It shows mileage affects price but only to a degree by the shape of the graph it appears a curved line of best fit would suite it better but I shall leave that to that.* Insurance group did have a positive correlation and quite a strong one at that, showing as the insurance group went up so did used price.ObservationsAs you can see on all of the graphs there are pieces of data that are way of the lines of best fit and away from the rest of th e data. I purposely kept this data in as it gives me a valid reason to do another sampling method. This data can be called anomalies as they differ from the rest of the data. I could cut this data out to make the sample fairer but then it wouldnt be a true random sample.With these observations made I can say a few things of what affects used car prices but now I shall move on and use a stratified sample and see if the data is more reliable.StratifiedA stratified sample is one where all the data has been put into an order and then a then picked out. For my stratified sample I have ordered them by mileage and then grouped the mileage and picked 40% from each group. This ensures I get 40 cars again so I can evenly compare the random and stratified samples.The mileage groups were. 0-50005000-10,00010,000-20,00020,000-40,00040,000-70,00070,000-110,000With these sorted I took 40% at random from each group and ended up with this. I ensured it was random by drawing numbers out of a hat resp ective to the numbers of the car, I then noted that number and placed in back in so each time the chance of drawing a single card was equal and didnt change. If I drew the same one twice I simply ignored that, placed it back in and redrew. (See Spreadsheet 3)If actually counted there are 41 cars. As 40 and 41 are very close, rather than tamper with any results which could make them biased I simply left them.From this data I then compiled scatter graphs on them just as before.Predictions* Age, I believe that there will be a strong negative correlation as there was before but as this is supposedly a more reliable sample it should be more evident.* MPG, I believe there will be a strong negative correlation as there was before but should be more evident due to sample being more reliable.* Mileage should have a strong negative correlation due to reasons above.* Insurance group should have a strong positive correlation due to reasons mentioned above.See graphs 5,6,7 and 8.Conclusions on S tratified Sampling.As you can see some very strange results came up.* Age showed the very strong negative correlation as I said there would be.* MPG showed a strong negative correlation as well as I said.* Mileage proved very weird. The data was in two groups basically one showing high mileage and low price while the other low mileage and low price. From this I can deduce that the mileage is a limiting factor of used price.* Insurance group showed no correlation with data all over the place, show perhaps my random sample was a mishap and in fact insurance has no relationship or very little with used price.ObservationsCorrelations were generally a lot tighter showing that stratified sampling alleviates anomalous data but can provide strange results, such as mileage for example. This result however may not be wrong but in fact right and the random results were wrong. To find out this I shall become more specific and look at another way of representing data.HistogramsAfter some thought a great way of comparing two sets of data and in a visual manner would be a histogram.To make a histogram I would have to group the mileages this however was easy as I shall take the groups I did for my stratifying of the data.The mileage groups were. 0-50005000-10,00010,000-20,00020,000-40,00040,000-70,00070,000-110,000I then made a tally chart with the groups and both random and stratified data.RandomMileage GroupTallyFrequency0-500015000-10,000110,000-20,000520,000-40,0001440,000-70,0001970,000-110,0002StratifiedMileage GroupTallyFrequency0-500015000-10,000210,000-20,000420,000-40,0001140,000-70,0001870,000-110,0005Then to construct a histogram I would have to work out the frequency density to go on the horizontal axis, this is worked out by.Frequency Density = FrequencyGroup WidthSo I ended up with this.Mileage GroupFrequencyFrequency Density.0-500011/5000=0.00025000-10,00011/5000=0.000210,000-20,00055/10,000=0.000520,000-40,0001414/20,000=0.000740,000-70,0001919/30,000-0.00063 70,000-110,00022/40,000=0.00005RandomMileage GroupFrequencyFrequency Density.0-500011/5000=0.00025000-10,00011/5000=0.000210,000-20,00055/10,000=0.000520,000-40,0001414/20,000=0.000740,000-70,0001919/30,000-0.0006370,000-110,00022/40,000=0.00005StratifiedMileage GroupFrequencyFrequency Density.0-500011/5000=0.00025000-10,00011/5000=0.000210,000-20,00055/10,000=0.000520,000-40,0001414/20,000=0.000740,000-70,0001919/30,000-0.0006370,000-110,00022/40,000=0.00005Mileage GroupFrequencyFrequency Density0-500011/5000=0.00025000-10,00022/5000=0.000410,000-20,00044/10,000=0.000420,000-40,0001111/20,000=0.0005540,000-70,0001818/30,000=0.000670,000-110,00055/40,000=0.000125Predictions* I predict that the random histogram will have a much more erratic distribution of car mileage while the stratified distribution will be more of bell shape displaying the majority in the mid range with low or no extreme values displayed.I then proceeded to draw the graphs.See Graphs 9, 10 and 11Results* As seen o n the two histograms there are some slight differences. The spread of the random sample is a little more erratic and uneven than that of the more bell shaped graph the stratified data shows. From this you could deduce that the stratified sample is a more reliable source of data than a random sample.* From individual graphs you can see that the majority of the cars are around the 20,000 to 60,000 miles range in both the random and stratified samples. Standard deviation could perhaps tell me which sample is more accurate so that could be an extension to the work done.* I mentioned a bell shape graph before. By this I mean one, which slowly goes up to a peak then reduces down, with the majority of the data displayed in the middle and only some or no data displayed in the highest and lowest areas.However from the histograms I did not find any reasoning behind the weird shaped and correlated stratified scatter graph. Further investigation into this could prove interesting.Overall Conclus ionFrom all the work carried out above you can clearly see that many different things affect used car prices and some more than others. You could say that the different categories are limiting factors and a culmination of these results in the depreciation of a cars price.As a further investigation I would look into the strange scatter graph produced by my stratified mileage sample. Perhaps using standard deviation or other data representation methods I could find out why it is so peculiar. I could also look at how one category affects another such as engine size and mileage or engine size and MPG and find a relationship between those. There are many more aspects that I could of considered but however from the work Ive done there are things that are certainly clear.