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BIOL 244 Absorbance Spectrum and Standard Curve Worksheets

BIOL 244 Absorbance Spectrum and Standard Curve Worksheets.

As the concentration of a substance increases, its absorbance will also increase. The exact relationship between absorbance and concentration for a particular substance is determined by creating a standard curve. To create a standard curve, first measure the absorbances of a series of samples with known concentrations using a spectrophotometer (this data is provided for you below). Then, graph each data point with concentration on the x-axis and absorbance on the y-axis. Create a line of best-fit. Now you can use interpolation to estimate the concentration of an unknown sample by measuring its absorbance (absorbance values also provided below).
BIOL 244 Absorbance Spectrum and Standard Curve Worksheets

A railroad car of mass M moving at a speed v1 collides and couples with two coup

A railroad car of mass M moving at a speed v1 collides and couples with two coup.

A railroad car of mass M moving at a speed v1 collides and couples with two coupled railroad cars, each of the same mass M and moving in the same direction at a speed v2.(a) What is the speed vf of the three coupled cars after the collision in terms of v1 and v2?(b) How much kinetic energy is lost in the collision? Answer in terms of M, v1, and v2.
A railroad car of mass M moving at a speed v1 collides and couples with two coup

Learner-guided approach to training

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Instructions

For the Unit I Essay, explain the learner-guided approach to training and its effectiveness in meeting organizational training needs. Within your essay, address the points below.

Describe training guides, self-directed learning strategies, and the use of smart technology.Describe two to three methods for organizations to harness the use of self-directed training. Why is this important?Explain how technology can be used to enhance the learner-guided approach to training. Select a field of study that interests you, and provide an example of technology being used to enhance the learner-guided approach in that field.

Your essay must be at least two pages in length, not counting the title and reference pages. You are required to use at least one outside source to support your explanation. All sources used, including required unit resources, must be cited and referenced according to APA standards

Relationship Between Police and Muslim Individuals

Shamma Alsuwaidi Dataset being used: 2014-15 Crime Survey of England and Wales Variable name of dependent variable: ‘copannoy’ Variable name of main independent variable: Muslim Word count of this project¹: 2,672 words I have included my SPSS output as an appendix to this project I am happy for an anonymised version of this project to be used for teaching purposes at the University of Kent My research question In this project, I examine the relationship between police officers and individuals from different religious groups. I will examine whether Muslims encounter more disturbing and discriminatory experiences with the police, compared to those who follow different religions (Christians, Jews, Hindus, Sikhs, Buddhists, and those who do not follow any religion). Accordingly, the dependent variable I will be using is: ‘really annoyed with the police’, while my independent variable will be: ‘Muslim’ religion. Potential mechanisms linking police malpractice to Muslims I selected these variables because in a post-9/11 civilisation, Muslims are increasingly becoming more segregated from societies as a result of the increased media attention to them. People began to fear Muslims and attempts to segregate them from society were made by many. Muslims are now perceived as an outsider group, a category of aggressive, extremist individuals, who pose a risk to ‘British’ lifestyles (Rowe, 2013). Although Islam is the most common religion amongst minorities, high rates of prejudice of Arabs and Muslims is evident in countries of the EU such as France and the UK. For instance, over 50% of people in Germany, France, and the UK identify and associate Muslims as radicals, aiming to promote their extreme religious beliefs (Jikeli, 2011). As a result, attitudes towards Muslims dramatically changed worldwide. Prejudice and hate spread, leading Arabs/Muslims to now face critical observation in every aspect of their lives. They can no longer travel, drive, and enjoy being out in public due to the discrimination they face in their everyday lives. In addition, instead of receiving support and protection from law enforcements, they are instead further victimised by them. Racial profiling, unjust treatment, unjustified investigations, harassment, and wrongful captures are now very common experiences between Muslims in European countries (Cainkar, 2002). In addition, it is not uncommon for an Arab to be ‘randomly’ selected for security checks at airports, and even be prohibited from flying due to such prejudice views. However, discrimination against those coloured and those who acquire divergent features than typical Europeans do occur as well; where gipsies (47%) and Africans (41%) experience higher levels of discrimination as well (Jikeli, 2011). I expect that Muslims are more likely to find themselves in situations where they become irritated by the police, or unsatisfied with how the police deal with occurrences compared to those who follow other religions. This is because, at a time of increased awareness and fear of terrorism, and with socially and politically constructed images of Muslims, society would ultimately treat them in a hostile manner. As a result, members of the law enforcement are more likely to share the same views with society or would be inclined into targeting and eliminating any potential harm or threat of terrorism that could be caused to society. Therefore, the police would be more likely to be suspicious towards an Arab or Muslim. Dependent variable In my analysis, I used data collected from the 2014/15 Crime Survey of England and Wales, which surveys adults (16 ) living in private residence in the UK. My dependent variable is ‘really annoyed by police’, which comes from the question: “Have you ever been really annoyed about the way a police officer behaved towards you or someone you know. OR about the way the police handled a matter in which you were involved? This might have been a police officer or another member of police staff.” 1. Yes- towards respondent 2. Yes- towards someone else 3. Yes- towards both respondent and someone else 4. No I am missing statistics on the frequency of police aggravation, since 24,806 out of 33,350 individuals did not respond to this question. Below is the frequency table of those who did respond: Number of responses Frequency (% of valid cases) No 6,341 74.2% Yes 2,203 25.8% Total 8,544 100% Table 1: Frequency table of police annoyance Since the question gives respondents chances to respond in different yet similar ways, I modified the way in which responses are interpreted. For example: * Yes: towards respondent │towards someone else │towards both respondent and someone else I integrated the responses in order to simplify the data. Instead of having various categories of the “yes” responses, they would all be integrated into an individual “yes” group. Therefore, my dependent variable is respondents claiming themselves, another individual, or even both being irritated by any staff within the law enforcement agency. 25.8% of the valid respondents stated that they have been in an experience where they, and/or someone they know has been annoyed by the police, as shown in Table 1. Main independent variable The main independent variable I am manipulating is the Islam religion. This is derived from the Crime Survey of England and Wales (2014/15), which is built upon individual’s self- reported religion, at the time they took part in the questionnaire. The question is shown as the following: “What is your religion, even if you are not currently practicing? CODE ONE ONLY IF YES, PROBE FOR RELIGION” 1. Christian (including Church of England, Catholic, Protestant, and all other Christian denominations) 2. Buddhist 3. Hindu 4. Jewish 5. Muslim 6. Sikh 7. Other (SPECIFY) 8. No religion Here, I am missing 76 responses out of the total of 33,350 people who took part in the survey. These individuals either refused to answer or claimed they did not know the answer. A frequency table of the remaining respondents can be seen in Table 2: Number of responses Frequency (% of valid cases) No 32309 97.1% Yes 965 2.9% Total 33274 100% Table 2: Frequency table of Muslim respondents As the question initially asks for their reported religions, I have created two distinct response categories. For instance, those with no self-reported religion, and those associated with other religions (Jewish, Christian, Hindu, Sikh and Buddhists), are categorised as “no”. Whereas, Muslims respondents are placed in the “yes” category. This is because I was interested in making a general comparison of Muslim and non-Muslim perception of the police, in order to carry out my analysis. Control variables In this section of my analysis, I added two further control variables, whether respondents live in urban or rural areas and their reported gender. Here, all 33,350 respondents answered the questions. This is achieved in order to explore other factors that could influence people to experience irritation from the actions or behaviour of the police. Although there was no precise question presented to determine whether a place of residence is in a rural or urban area, respondents had to describe the features of their neighbourhoods and provide their address (postcode) on the survey. As a result, rural areas come to be defined as areas where the population is less than 10,000; communities where 7,567 (22.7%) of the respondents inhabit. However, exploring gender was based on the following question: “CODE THE SEX OF EACH ADULT IN THE HOUSEHOLD IF NECESSARY: Is (name) male or female?” Male Female Here, the interviewer collects data on every member of a household, assuming their gender, unless they are uncertain. This data indicates that 45.1% (15,030) of the 33,350 respondents are males. Analysis Part I: In my first stage of analysis, I examine the pattern of irritation from the police, by association of the Islam religion. The link between being a Muslim and the likelihood of being annoyed by the police is analysed by using a Crosstabs, as shown in the table below: Table 3: Link between police annoyance and Muslim religion Have not been annoyed with police Have been annoyed with police Total Non-Muslim 74.0% 26.0% 100% Muslim 84.0% 16.0% 100% Total 74.2% 25.8% 100% Total number of respondents for this analysis: 8521 Although 24,829 people did not answer this question, Table 3 shows data based on the 8,521 individuals who did. 16.0% of Muslim respondents claimed that they encountered a situation where an officer annoyed them, or someone they knew, in comparison to 26.0% of non-Muslim respondents. In other words, Muslims are 10% less likely to claim to be annoyed with an officer of the law, than those of other religions; resulting in a different pattern than I predicted at the start of my analysis. Analysis Part II: Is this pattern systematic? Data suggests that members of the Muslim community are less likely to be annoyed by the way police handle situations than others. However, this could have resulted from the randomness of the sample, or randomness of how police members handle occurrences and behave towards people. So, I ran a regression with being annoyed with the police as the dependent variable, and being Muslim as an independent variable; to examine the pattern’s certainty. A table below discloses whether the pattern in systematic: Coefficient (B) 95% confidence interval Constant 0.260 0.251 to 0.270 Muslim -0.100 -0.157 to -0.043 Table 4: Regression table of influence of police annoyance In Table 4, we can see that the estimated effect correlates with the mean difference in the likelihood of being annoyed with the police, in the previous part; Muslims are -0.100 (-10%) less likely than those of other religions, to state that they have been ‘really annoyed’ with the police at one time. In addition, the regression table produces a confidence interval around this data; -0.157 to -0.043 (-15.7% to -4.3%). Since the figure (-0.100) lies between the confidence range, this data implies that we can be quite confident that Muslims experience lower levels of police annoyance, in a systematic manner: If we could create 100 worlds, and re-run the patterns, the true value would lie within the range (-0.157 to -0.043) 95 out of 100 times. Which, therefore, suggests that being Muslim decreases an individual’s likelihood of being annoyed by the police, 10% less than those of other religions. In addition, as both figures in the confidence intervals are negative and the range is narrow; this allows us to be quite confident that the pattern is systematic. However, we cannot be 100% certain. Analysis Part III: Is this pattern causal? There are other possible factors that could explain the correlation between Muslims and dissatisfaction in how police handle situations. These confounders vary from the mechanism I examined earlier; around police interactions around Muslims. For instance: An individual’s area of residence could impact the way the police interact with them. It is more likely for those living in deprived areas to experience injustice from the police, and therefore, hold negative images of police officers. They are also more likely than those in urban areas to have issues with police officers, as their neighbourhoods are likely to have high rates of criminal activities. In addition, police staff may be prejudice against people living in rural areas, labelling them as criminals, and therefore, treating them in a different manner. It could also be due to gender. As female criminality is not as common as those of men, police are known to focus on male suspects. Especially as there is a high rate of young male offenders in this century, male suspects are more likely to be annoyed by the police. In order to test both hypotheses, a further regression was carried out, which includes neighbourhood area (urban) and gender (male) as control variables (as defined above). Coefficient (B) 95% confidence interval (Constant) 0.141 0.081 to 0.202 No religion 0.147 0.089 to 0.206 Christian 0.077 0.019 to 0.134 Hindu 0.012 -0.088 to 0.111 Other religion 0.109 0.021 to 0.197 Lives in urban area -0.017 -0.039 to 0.005 Male 0.073 0.054 to 0.091 Table 5: Regression model of influences of being annoyed by the police We can see the impact of my control variables, as shown in Table 5: Living in an urban area: living in urban the areas, is associated with a decrease in being annoyed by the police by 0.017 (1.7%). Although this effect seems minimal, it could increase dramatically depending on how rural/urban an area is labelled as. However, here, we cannot be confident that the pattern is systematic, due to the confidence interval containing positive and negative figures (-0.039 to 0.005). Gender: males in the community are more likely than females to be annoyed with the police, or how they handled a situation; 7.3% (0.073). Here, we can be very certain that the pattern is systematic because the confidence interval range is very narrow. In order to concentrate on my main area of interest, I pay particular attention to the difference in how the police deal with those of varying religions. We can analyse a contrast among both versions, in a chart shown below: Coefficient (B) 95% confidence interval Original model (no controls) -0.100 -0.157 to -0.043 Second model (with controls) -0.099 -0.157 to -0.042 Table 6: Comparison of effects of police annoyance on Muslims This suggests that the gap in how police interact with those of different religions, is almost identical in both models; whereas, in the original model, Muslims are 10% (-0.100) less likely to have been annoyed by the police, and 9.9% less likely when controls are added. We can still be quite confident that Muslims are less likely to have been annoyed by the police, as the confidence intervals in both remain almost unchanged, and remain narrow. This indicates some proof of causality; however, we cannot be 100% confident. While keeping reverse causality in mind, to further investigate whether there is a causal effect, we can be quite certain that it does not apply in this context. In other words, we would not infer that experiencing a dissatisfying experience with a member of the police causes an individual to become Muslim. Limitations

University of Oxford Effective Communication in the CNN Company Discussion

University of Oxford Effective Communication in the CNN Company Discussion.

I’m working on a communications discussion question and need a sample draft to help me learn.

Watch the video (in its entirety) posted in the link belowUndercover Video CNN technical director (Links to an external site.) https://www.youtube.com/watch?v=Dv8Zy-JwXr4&t=5s (Links to an external site.)Charlie Chester CNN article (Links to an external site.) Write a 300-500 word response to what you saw.How do you feel after viewing this?Was this surprising to you?Do you think anything should happen to CNN?You are allowed to have and share any opinion you want! You can’t be “wrong”. It is your opinion and you have a right to it.When you respond to 2 classmate’s posts just be mindful of your words should you strongly disagree with someone else’s thoughts and feelings on the matter. It is OK to disagree!* If you would like to do further research on this topic just look up Charlie Chester CNN and many articles and videos will be available for you to choose from on Google. Read to see what the latest is on this current controversy.
University of Oxford Effective Communication in the CNN Company Discussion