Sunday, December 29, 2019

Using Technology For Managers ( Adm 310-01a ) - 1345 Words

Ethics Bryan E. Cratty Russell Ray BSM767 Appld Technology for Managers (ADM-310-01A) November 23, 2015 I have read and understand the plagiarism policy as outlined in the syllabus and the sections in the Student Catalog relating to the IWU Honesty/Cheating Policy. By affixing this statement to the title page of my paper, I certify that I have not cheated or plagiarized in the process of completing this assignment. If it is found that cheating and/or plagiarism did take place in the writing of this paper, I understand the possible consequences of the act/s, which could include expulsion from Indiana Wesleyan University. Technology plays a huge role in today’s society. We use technology for several different reasons whether it is personal or business. When we have important protective documents, we have to protect them with passwords. Passwords must be strong and complicated, so hackers are not able to access our secure documents. It is very important to have strong password etiquette but should also be easy to remember. Strong passwords contain special characters and numbers. In Shakespeare’s Macbeth, the line â€Å"Tomorrow and tomorrow and tomorrow, creeps in its petty pace† can be used to make a strong password. To use this, you will need to add numbers and special characters. Using tomorrows date you can create a strong password that is easily remembered by using the day as the number and the @ as a special character. For example, you could have the

Saturday, December 21, 2019

Monism, Dualism, and Pluralism in American History Essay

It seems readily apparent that monism is without a doubt the very worst way to approach history, Societies and cultures are not one dimensional, but rather are made up of a tapestry of factors. Thus looking at just one aspect gives the historian only a myopic sense of what was going on or what people were thinking at a particular time or place in history. While this is typically thought of as being the consensus history of the great white men, however other schools of historical thought can also be viewed objectively, as being equally narrow in scope. One simply can not expect to garner a panoramic perspective of history by looking at it solely from one perspective. Its illogical to think that a private in Washingtons army saw the war†¦show more content†¦A dualistic view of history is a better way of looking at history, but still excludes any number of factors and perspectives and thus is of somewhat limited use in uncovering the full story of the past as well. Progressive historians of the early 20th century, many of whom were heavily influenced by Marxist theory, were the first to look at American history from a dualist perspective, followed in later years by Marxist, Neo-progessives and the New Left historians. They saw a great deal of division in early American society in sharp contrast to the united front standing behind the patriot elite, which had previously been ingrained by the romanticized visions of earlier nationalistic writers. They emphasized this division in American society which had existed well before the revolution and remained a constant factor in the make up of our nation, indeed it remains that way today. Much of this type of history attempts to look at history from the bottom up, that is from the perspective of the working classes and this carries with it the inherent problem of locating primary sources. While the papers and documents of historically prominent people are almost invariably collected and archived, the same is can not be said for the personal effects of average citizens. Therein lies the main weakness of this type of history, however it opened minds and brought new ideas and visions

Friday, December 13, 2019

Mexican Drug War Free Essays

Since Felipe Calderon became the president of Mexico in December of 2006, more than 30,000 people have died in this nationwide turf war. A large majority of these murders are happening in the states of Chihuahua and Baja, California both of which border the United States. Soon after Calderon took office he launched a military-led war on drugs and that set off conflicts all over the country between rivaling cartels. We will write a custom essay sample on Mexican Drug War or any similar topic only for you Order Now Not only has there been a war between the cartels, there’s an overall threat to all of the citizens of Mexico because nobody is above the hell these savages are unleashing. All across the southwest United States the drug cartels have been smuggling drugs and weapons between countries illegally. Within the last month U. S. and Mexican authorities unearthed a 2200 ft. long tunnel under the border. This tunnel was used to smuggle drugs into San Diego, California where cartel commanders distribute the marijuana throughout the country. Then going back into Tijuana, â€Å"mules† would carry guns back. This tunnel was state-of-the-art with air conditioning, ventilation, and tongue-and-groove boarding to keep the ground level for the safe transportation of the weed. Other than weed; heroin, cocaine, and guns are also transferred between borders. 70,000 U. S. -originated firearms were recovered between 2007 and 2009. Along the two thousand mile long border between the United States and Mexico there are over seven thousand licensed gun dealers on the U. S. side. Just like the drugs moving North, the guns are flowing South in the trunks of cars, under the beds of truck, and sometimes hidden by clothing in the floorboards of cars. The main thing issue with these cartels is that innocent men and women are dying every day for the sake of a dollar. Some of these people that are dying were totally in the clear and had nothing to do with Mexico, they were just vacationing. Two students who attended the University of Texas in El Paso were hiking through the mountains and accidentally crossed over the wrong hill at the wrong time and that cost them their lives. Along with those two students, the US State Department released a statement saying eighty other American travelers had been murdered in Chihuahua alone. Even Mexican citizens are dying for no reason. A group of twenty vacationers from Michoacan, Mexico were visiting Acapulco and a group of armed assailants snatched them up and took them away. The only reason the men’s bodies were found is because two severely beaten men made a video and broadcast it on YouTube in hopes that somebody would find the mass grave. This group of men died all because their kidnappers thought they were henchmen for a rival cartel. The United States being involved in the Mexican Drug War shows all six steps of the government function: Foreign relations and diplomacy to help with military defense while they try to gain control of the country. Developing business strength while controlling the cartel interactions is another part of the government function. Oil is a major natural resource in Mexico, so helping keep it protected also while keeping its use under control. Another thing is the enforcement and regulation of fair and responsible business practice to handle the legalities of NAFTA in check when necessary. Since the United States feels the need to be a global police state, we also help determine and enforce the laws and help citizens gain more rights. And most importantly, provide public goods and services for the well-being of the community as a whole. Things that the National Guard is there to help with, like vaccination programs, disaster relief, and basic healthcare. The primary policy that would have helped our nation and the drug war was California’s Proposition 19. Proposition 19 also known as the Regulate, Control, and Tax Cannabis Act was wanted for the decriminalization of marijuana for specific purposes. Many people argued that it would help with cut off the funding to the violent cartels along with helping out California’s budget shortfall and redirecting law enforcement’s resources to more dangerous crimes. While opponents claimed that it contains gaps and flaws that may have serious unintended consequences on public safety, workplaces, and federal funding. However, even if the proposition had passed, the sale of cannabis would have remained illegal under federal law via the Controlled Substance Act. Being active in the Mexican Drug War hasn’t helped the approval rating of the government much at all. Two things dealing with Mexico and its citizens that aren’t helping the public opinion are the DREAM Act and the US Merida Initiative. The DREAM Act is a bill proposed by the House of Representatives that would give citizenship to immigrants who moved into the United States as a minor, have graduated from high school, and are on good moral standings. And the U. S. Merida Initiative s planned cooperation between the United States, Mexico, and countries in Central America with the aim of combating drug trafficking, transnational organized crime, and money laundering. It may sound good, but the government has funneled more than $1. 4 billion into this initiative. Yet the US Department of Education has to cut spending in half? Our government is obviously overstepping its boundaries, when is it not? For example Homeland Security’s Immigration and Customs Enforcement division (ICE) was created to shore up the borders after September 11th. But forced drugging and warrantless raids weren’t part of the mandate and in May of 2008, the Washington Post reported that there have been more than 250 cases of the government giving deportees psychiatric drugs with no medical excuse or reason. Yet ICE itself disputes that number of cases and says that only 180 out of close to 600,000 were involuntarily sedated. Another way the government is overstepping its boundaries is with the legalization of medical marijuana in California. Not the fact that it’s legal, but what happens to those who need it and use it. Those who are medically permitted to have marijuana and travel within seventy-five miles of the Mexican border have to deal with Border Patrol and their â€Å"Fourth Amendment-free Zone†. That permits warrantless searches to any and all comers in a bid to stop illegal immigration and drug smuggling. Patients and advocacy groups are complaining that the border area checkpoints operated by the Border Patrol are sweeping up patients, detaining them, seizing their medicine, and sometimes arresting them on federal drug possession charges. How to cite Mexican Drug War, Essay examples

Thursday, December 5, 2019

Commuters Cycling Behavior Response to Weather Variation

Question: Discuss about the Commuters Cycling Behavior in Response to Weather Variation? Answer: Introduction This report is about business cycle prediction in Sweden. Binary logistic regression method is used in this research paper for all the related statistical analysis. All the variables of interest are chosen with proper care and the significance of selecting each variable is analyzed and judged statistically. Researcher restricts the size of the test at alpha=0.05. In a binary business cycle operation, only 0 and 1 value are taken to predict outcomes. 0 value signifies an expansion in economic activities in a near future time period, 1 value codes the contraction in economic activity. The probabilities are derived from a number of variables that could have an impact on the real economy. Several related references are compiled at the reference list. Interpretation of log likelihoods If the independent variables have a relationship to the dependent variables, the ability to predict the dependent variable accurately will improve, and the log likelihood measure will decrease thereof. The model fitted on quarterly data and the results of predicted and observed values are tabulated under recession and expansion outcomes. Expansion shows 82% and recession shows 75% correct prediction, and the overall correct percentage is obtained 78.9%. Whereas in the case for monthly data, proportion of expansion and recession is 86% and 78.3% correct respectively. Over-all correct percentage is 82.6%. However, the log likelihood value for monthly data is 186.9, which is considerably large than that of quarterly data (68.2). Quarterly data model is thus, a better fit than monthly data model. Note: -2 log likelihood is termed as badness of fit. The value below 100 indicates good fit and value under 20 ensures very good fit (Scott and Varian 2014). Interpretation of classification tables In a binary classification, type I and type II errors are false alarms being positive and negative respectively. Not predicting a recession, which is likely to occur is type I error, and predicting the occurrence of false recession is type II error in this context. Almost 60% of total observations are correctly categorized in quarterly periodicity, and almost 56% of recessionary periods are properly categorized in prediction. The values for monthly periodicity are 76.5% and 75.9% respectively. Quarterly period has a proportional measure of 41% and the monthly period has the same measure of 21.2% in the context of the recessionary periods being false alarms. Monthly data consists of a sample size, which is three times larger than that of quarterly data at the same time span. For any economic decision to predict recession or expansion, researcher needs to know at least the information of past 3 months in advance (Billio et al 2013). Difference in variables between model The variables are used in both quarterly and monthly data models are the same but they differ in lag measures. The differences in selecting the variables in the sensitivity analysis are listed below in a table format. Quarterly data model Monthly data model Europe GDP(3) Confidence (3) Oil(4) Europe GDP(8) OMX(1) Oil(12) Confidence(1) OMX(1) Spread(1) Spread(1) Building(1) All the variables listed in the above table are statistically significant at 5% level. The values in the brackets indicate the time lag for each individual variable. Minimum three months lag is needed. Confidence (1), OMX(1), Spread(1) variable and results in quarterly and building(1), OMX(1) and spread(1) variable for monthly are thus not so statistically reliable (Hamberg and Verstndig 2009). Interpretation of the coefficients The Logit function for the quarterly data can be expressed as, Lq(X) = 2.7- 115spread(1) 4.2OMX(1) + 2.99Oil(4) 55europeGDP(3) 0.05confidence(1) The logit function for the monthly data can be formulated as, Lm(X) = 3.01- 103spread(1) 4.3OMX(1) +2.8 Oil(12) 65europeGDP(8) 0.07confidence(3) 1.73building(1). OMX, spread, confidence, building and Europe GDP variables are expected to have a negative sign. That means, the associated variable if increases, there will be a lower probability of falling into economic recession. Similarly, it can be stated that higher value of the associated variable intrigues higher probability to fall into recession. The Oil variable is likely to have a positive sign. If the price of oil increases, the problem can be depicted as a supply shock and it can be responsible to affect economy negatively. Analyzing the models researcher can claim that all OMX, spread, confidence, building and Europe GDP variables are associated with negative signed coefficients. In both the models, Oil variable is merged with positive valued coefficient. It can be concluded that both the models are fitted according to requirements and they are reliable (Tang and Shen 2014). Interpretation of the coefficients P-values Probability of rejecting the null hypothesis is called the p value of the test. To find the validity of Beta coefficients two types of hypotheses are formulated, they are Ho : beta equals to zero H1 : beta not equals to zero. Generally, the value of alpha is taken as 0.05. If the estimated p value is less than 0.05 or 5%, it provides enough confidence to reject the null hypothesis. In this analysis, not all the estimated p values are only significant at 5% level, they are so in the 10% level too. The null hypothesis that beta=0 can be rejected. In addition, the findings show beta values are not zero. It signifies the variables of interest in the particular study have some predictive powers. Largest beta coefficient suggests it has the greatest effect on the likelihood (Berge 2015). Time lags Time lag has an important implication in the forecasting model. Generally, a lag of 3 is considered as statistically significant. According to the definition, a model fails to predict any further into the fore coming than its terse lag. In this report, the shortest lag implemented is one quarter and one month for the monthly data. This suggests that the models should not be used to forecast any further events ahead than that lag. The Europe GDP figures here are lagged for two months. This fact confirms that a forecast implying a point of turning, which might actually appear at least three months earlier the actual GDP data has been published. Greatest impacts If the regression beta coefficient is positive, the interpretation is that for every 1-unit increase in the predictor variable, the dependent variable will increase by the non-standardized beta coefficient value.Largest beta coefficient suggests it has the greatest effect on the likelihood. From the logit model described above, a logit function can be derived as, P= eL(X)/ (1+eL(X)) Lower value of the logit function ensures less probability of falling into recession. The larger the beta coefficient is, it is likely that there will be more impact on recession. The coefficients with the OMX, spread, confidence, building and Europe GDP variables have negative sign. Proportion of recessionary periods correctly categorized in monthly data model is 75.9%, which is greater than that of quarterly. Monthly data model variables have thus greatest impacts and they are reliable to predict proper recession issue. Dichotomous In this type of analysis researcher tries to predict which variables in both models are likely to depict recession or expansion of the economy. The Europe GDP variable has a negative beta coefficient. Thus, if there is any increase in GDP, it will reduce the likelihood of the recession. OMX, spread, confidence and building variables too have negative beta value, so increase in all these variables will shorten the likelihood of recession. The Oil variable has a positive beta coefficient. Thus, increase in the Oil variable will also increase the likelihood of a recession. The variables in both monthly and quarterly data model are fitted properly with the expected signs. Researcher can justify that the models confirm that the current economy under study, is expansionary (Ahmed, Rose, and Jakob 2016). Report layout The time series predictors found in the in sample analysis are examined in contrast to the actual primary observations for the same time period. The integral model on monthly data explained above has a sample, which is three times larger as the one for the quarterly data model. By using this type of sample, monthly data model predicts almost 83% of the observations properly. In the out of sample prediction, the results from quarterly data can be viewed as weak. Comparatively frail out of sample forecast for quarterly model can be ascribed to the reduction of sample size. Conclusion As a conclusion based on the above discussions, researcher believes that the monthly data model consisting greater number of observations implements really well. The building variable is not significant enough with only (1) time lag. Other reason for the insignificance is building a house is a decision of long term and it should be planned in advance assorted years before the construction takes place in reality. Monthly data model ensures the findings in the main model excluding the building variable are indeed significant. The quarterly model is less sensitive to any changes in the dependent variable. A logistic regression model with the quarterly data set has multiple notable features. The results derived from the model should be considered as a guideline but not an absolute legitimacy (Scott and Varian 2014). References Ahmed, F., Rose, G. and Jakob, C., 2016. Commuters' Cycling Behavior in Response to Weather Variation: Insight from an Extended Theory of Planned Behavior. InTransportation Research Board 95th Annual Meeting(No. 16-5484). Berge, T.J., 2015. Predicting recessions with leading indicators: model averaging and selection over the business cycle.Journal of Forecasting,34(6), pp.455-471. Billio, M., Ferrara, L., Guegan, D. and Mazzi, G.L., 2013. Evaluation of Regime Switching Models for Real Time Business Cycle Analysis of the Euro Area.Journal of Forecasting,32(7), pp.577-586. Hamberg, U. and Verstndig, D., 2009. Applying logistic regression models on business cycle prediction.Unpublished master's thesis, Stockholm School of Economics, Stockholm, Sweden). Retrieved from https://arc. hhs. se/download. aspx. Scott, S.L. and Varian, H.R., 2014. Predicting the present with bayesian structural time series.International Journal of Mathematical Modelling and Numerical Optimisation,5(1-2), pp.4-23. Tang, J. and Shen, L.P., 2014. Application of Business Risk Prediction Model: Based on the Logistic Regression Model.International Journal of Business and Management,9(7), p.139.