State Of Colorado s Current Gsp - 1316 Words

Mary Jane Shively ECON 204 October 7, 2014 Writing Assignment #1: State Analysis Part 1: State Output: Gross State Product Gross State Product (GSP) is a measurement of the economic output of a state or province, and is the sum of all the value added by industries within the state. The current level of GSP in New York available is 1,310,712 million in 2013, showing a 2.3% change from 2012 GSP. The 1-year change represents an increase in gross state product by about 29,975 million dollars. In order to further understand these values, it is important to compare them with another state. The state of Colorado’s current GSP is 294,443 million, which is significantly lower than New York. However, when comparing the two states, it is important to factor in population size. New York has a much larger population than Colorado, and therefore GSP per capita may be better way to compare the two states. New York’s GSP per capita is 62,212 million and Colorado’s is 51,956 million according to the U.S. Department of Commerce: Bureau of Economic Analysis. While GSP per capita allows for a more accurate comparison of the two states, New York’s GSP and GSP per capita still exceed Colorado’s by a wide margin. New York could have these high levels of GSP for a number of reasons including: a larger population, more international trade, and being home to one of the largest cities in the world. All of these factors allow New York to produce more goods and services annually, resulting in a highShow MoreRelatedEconomic Health Of Oregon By Looking At Gross State Product, Unemployment, And Inflation Essay1082 Words   |  5 Pagesproduced contributing to Gross State Product. Inflation is an indication because it determines how much real value is being lost(Graham). In this paper I will analytically discuss the economic health of Oregon by looking at its Gross State Product, unemployment and cost of living. Gross State Product(GSP) is the total dollar value of all final output produced within a state in a certain time period, usually one year (Schiller). The aspects that contribute to a state’s GSP are all private and publicRead More It Is Time To Legalize Marijuana Essay2824 Words   |  12 Pageslegalized. During the time of illegalization of marijuana, the drug had a vastly negative feeling associated with it, which many people now believe to be inaccurate and unfair. Now that people are more informed, more connected and more vocal, the United States government should allow and even encourage more research of the dangers and addictive nature of the drug which will assuredly legalize medical use and possibly recreational use to benefit people and the economy greatly. This paper will discuss many

Does Ghost Exist in Real Life Free Essays

Does ghost exist in real life? It has been a popular question been ask for few decades. Some people encounter the supernatural phenomena, some not. So there are people who believe and people who disbelieves. We will write a custom essay sample on Does Ghost Exist in Real Life? or any similar topic only for you Order Now Therefore, here are some introduction of what ghost really is, where we can find their existence, how can we feel their presence and does science proof the existence of ghost. In traditional belief and fiction, a ghost (sometimes known as a spectre (British English) or specter (American English), phantom, apparition or spook) is the soul or spirit of a dead person or animal that can appear, in visible form or other manifestation, to the living. Descriptions of the apparition of ghosts vary widely from an invisible presence to translucent or barely visible wispy shapes, to realistic, lifelike visions. The deliberate attempt to contact the spirit of a deceased person is known as necromancy, or in spiritism. The region that ghosts, demons, devils, and negative energies occupy or come from, varies depending on their spiritual power, capabilities and so on. Any being such as human being or subtle body that feels comfortable in their respective region because their frequencies correspond to that region. With increasing spiritual power, the ghosts become even more subtle and are found in progressively deeper negative regions. Thus ghosts who have the least spiritual power are found in the Nether region. The ghosts that exist in the deeper rungs of Hell are progressively more powerful and evil. There are few theories about ghosts. Many believe that non-reactive apparitions of people that seem to do the same things over and over are some form of energy-imprint on the environment. This type of ghost manifestation is known as a non-intelligent haunting or a residual haunting, and is called such due to the lack of interaction between the ghost and the living. This type of ghost is not dissimilar to a video playing over and over, ever seeming to repeat itself. Could these types of ghosts have been produced by strong thoughts created by people while living, and continuing to exist within the atmosphere in some form or fashion? This theory concerning ghosts remains unproven. We ponder if it is also possible that this type of ghost is just trapped in time, unable to communicate or interact with the living due to severe emotional trauma – a self-created mental prison, if you will. Both ghost theories regarding non-reactive ghosts will have to be worked on in the future to see which has merit. Another type of ghost is called a poltergeist, which many believe to be the projected psychokinetic energy of a living person that creates movement of objects and various noises. Though the word â€Å"poltergeist† is German for â€Å"noisy ghost,† this type of phenomenon is not attributed to ghosts by those who have studied such accounts. It seems true poltergeist haunting activity is typically centred around a female adolescent in the home who is unwittingly producing the disturbance. The disturbance typically ceases over time, as the adolescent ages. A theory regarding ghosts centres around the previously described condition the earthbound spirits find themselves in. For these reasons, we believe many a haunting occurs, as ghosts are suffering and in need of assistance in easing the emotional pain. We believe that we are finding most ghostly activity, such as noises, dreams, visible appearances, various disturbance, communications, touching, and even attacks, can all be explained by coming to understand the desperate minds of pained, disembodied spirits. They are simply people in need of spirit rescue. Ghosts exist in a variety of places on Earth. They can create a centre for themselves in living and non-living objects. By centre we mean a place where they store their black energy. The centre acts as an entry point and a point of receiving or transmitting their black energy. Ghosts generally create a centre for themselves in people, trees, houses, electrical equipments etc. When they create a centre for themselves in people, it is to fulfil their desires such as eating, drinking, smoking, sex or to settle a give-and-take account. Since the ghosts are made up of the Absolute Air element, one cannot see them without subtle vision. When people repeatedly experience various forms of inexplicable distress, around a place, person or object, it is very likely that the place, person or object is affected or possessed by a ghost. Feelings of distress include feeling of apprehension, feeling a presence, feeling like one’s entire energy is being sucked out or repeated mishaps happening in a certain place, without any apparent reason. The actual presence of the ghosts is however evident only to those with an activated sixth sense. The ghosts there cause distress to those who come in the vicinity or possess them, especially those who are vulnerable psychologically such as anxious and depressed or spiritually whereas people with low spiritual level are easy to get affected or possessed by ghosts. Nowadays, modern technology has rushed to the rescue by providing ghost hunters with myriad devices to capture the images, videos, and voices of ghosts. Unfortunately, tricksters and frauds have used the same technology to fool a number of people. No wonder that genuine evidence that ghosts exist is being dismissed as fraud material. People, especially those with a scientific or rational background, tend to dismiss any explanation that ghosts exist with disbelief and amusement. There are some scientific proof that ghost exist in the form of energy. The law of thermodynamics, if examined from a different angle, could prove that ghosts exist. Even if it cannot be taken as proof, it could give rise to a number of questions. If these questions are taken seriously and attempts made to find answers to them, we might very well come up with proof that ghosts exist. The law of thermodynamics is the most significant law among the gravitational laws. A careful study of it reveals the fact that science has already proved that ghosts do exist. According to this law â€Å"Energy can neither be created nor destroyed; it can only change form. † Let us now analyze this law carefully. Energy never dies, according to this important law; instead, energy shifts from one form to the other. Accordingly, the energy that we are is not destroyed by death; it just changes form. Skeptics would say that our bodies would be decomposed by the action of the microorganisms, and this is how human energy would change form. But, what about the intelligence that gives us an identity? Just consider the amazing nature of our minds and bodies. Would all this just end up as being fodder for the microbes? Does this sound like a fair exchange? The more one questions, the more one feels that there is more to life than what meets the scientific eye. In conclusion, other theories regarding ghosts do exist, such as ghosts being simply the creation of the overactive mind, hallucinations, carbon monoxide poisoning, exposure to low frequencies, etc; but we are seeing too many pieces of the puzzle come together that cannot be explained away in total by the various, sceptically theories. We ask ourselves the age-old question, â€Å"Do ghosts exist? † But in the end, realistically it’s impossible to say whether ghosts are real or not. It’s all down to the beliefs of the person themselves. To me and my experience of Ghosts or Spirits is of that they do exist, because of some experiences I have had in the past. However to many others with no experience it may be seen as total rubbish. How to cite Does Ghost Exist in Real Life?, Essay examples

Highline Case Study free essay sample

Define the Problem: Highline Financial Services, Ltd. offers three diverse services to its clientele. We are given the demand for the three services over a two year period broken down into four quarters each totaling eight quarters of data. Given this data, we are asked to forecast the following four quarters for year three and explain the observations made. However, we must assume that Highline Financial Services, Ltd. has not made any changes in advertising, promotion or competition. For this problem we look to try and gather an estimate of what the best forecasting method will be for the demand of services A, B, and C. The methods of analysis used to attain the figures include; linear regression, regression model, and forecast error analysis. Plan the Treatment: In order to apply all of the demand forecasting methods properly and acquire the most accurate demand forecast, we must do the following†¦ Graph historical demand – define the key data elements. We will write a custom essay sample on Highline Case Study or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Define the time horizon – forecast must include a time interval. Clean the Historical data – there usually exist problems with the quality and completeness of data, â€Å"clean† (remove) all data that is found unnecessary to the forecast. Select a forecasting technique or multiple forecasting methods. Make the forecast. Execute: In order to make the best forecast possible, it is imperative to understand the past demand in order to better see what type of data and trends to look for. Linear Regression attempts to model a relationship between two variables; the dependent variable (y) and an explanatory variable (x). Linear Regression allows for a visual look into the linear trend of a forecast. It formulates the best-fitting straight line for the plotted data. Linear Regression allows for a visual view in determining whether the trend is ascending (positive) or descending (negative). Thus, we are already given clues that adjustments for trends may be necessary. Now that the demand data has been analyzed, I will begin to explain the three methods of forecast mentioned in the section (define the problem). Static Regression Forecasting: We now perform a static forecast of the demand data to give us a model which has level and trend as constants. These parameters are based off historical data provided, and held constant for the forecasting of new demand. The static forecasts for services A, B, and C are shown below. The steps necessary to obtain their values are used with the regression tool in excel. First you plot the x and y coordinates into an excel spreadsheet. Afterwards, you would select the demand data, click on the Data tab – Data Analysis Tab – Search for Regression – Input the y and x range – Click Ok. Once these forecasts have been made, we can stack the forecasting method against the actual demand to observe its effectiveness. Service A: Service B: Service C: Deseasonalizing: Seasonal variations are â€Å"regularly repeating movements in series values that can be tied to recurring events† (Stevenson). However, our demand data lacks the information used to develop seasonal relatives. Thus, in order the remove the seasonal component from a set of data, one would deseasonalize the data. Deseasonalizing data allows for a clearer representation of the non-seasonal (trend) components. In order to obtain deseasonilzed demand for the forecast one must divide the demand data by the seasonal relative. The resulting values from this equation were calculated in excel and are shown below. The tables descend from Service A BC. Deasonalized demand for quarter three in the table above was obtained by taking 100 and dividing it by 1. 40056. D1= 100/1. Now that the regression results are obtained, we have the equations to get the deseasonalized regressed demand equations. The equations are: Service A: 64. 2 + 2. 4x Service B: 90. 2875 + (-2. 425)(x) Service C: 98. 3875 + (-0. 6)(x) To find the average seasonal factor for each quarter we simply take the same quarter of every year and average all of them together. Once the average seasonal factors are obtained, you can obtain the re-seasonalized data forecasts by multiplying the regressed demand against the average seasonal factor for each period. This acquired demand data is now used as your forecast demand. Forecast Error Calculation: Error analysis can provide a helpful look at the effectiveness of a forecast as it tells us how our forecasting method statistically stacks up against the actual demand data that we have been given. If the error analysis comes back with low errors, we know we have created a good forecast. The methods for finding these error values are shown below: Error: is found by simply subtracting the forecasted demand against the actual demand. Absolute Error: Absolute value of the error. Mean Squared Error (MSE): States the variance (square root) of the forecast error, and is calculated with the following equation, MSE= ? (Actualt – Forecastt)2 / n-1 Mean Absolute Deviation (MAD): is the average absolute forecast error solved with the following equation, MAD =? |Actualt – Forecastt| / n Mean Absolute Percentage Error (MAPE): determines whether a forecast is consistently over-estimating or under-estimating the demand. The equation is as follows, MAPE= (? |Actualt Forecastt| / Actualt) *100)) / (n) % Error: Measures the percent difference between the absolute error and the actual demand. Solved by the following equation: %E= 100*(Absolute Error/ Demand) Conclusion: Overall, Service A appears to be increasing and should continue to increase over the next year (four quarters). According to the Adjusted R Square, the model is an A model with a score of . 996104. Service B appears to be decreasing annually and the data demonstrates that it will most likely follow a decreasing pattern. However, although Service B has a negative slope it is also the best rated model with and Adjusted R Square of . 99666. Service C shows an inconsistent demand pattern. Service C was also rated as an F model with an Adjusted R Square of .  229114. In addition, Service C is very scattered and has a high mean absolute deviation. Concern: In general all three services follow a trend. However, according to the forecasted data, Service B poses the greatest risk of concern. Service B continues to follow a downward linear trend in both the historical data and the forecasted data. Thus signifying that demand for Service B will continue to decrease. Simply, Service B has little opportunity for growth and anticipates a decline in profit. In addition, even though Service C follows an inconsistent pattern, overall it continues to follow a minimal increase in its linear trend. As mentioned earlier, Service C was rated as an F model, thus suggesting that there is room for improvement. If improvements are made the model will increase to a level closer to 1. 00 or 100% thus making it a better model. Eventually, there might still appear a scatter in data however the demand will continue to increase with a positive slope. Forecasting: Forecasted data is only an estimate, can and is subject to change. Works Cited: Stevenson, William J. Operations Management. 11th ed. New York: McGraw-Hill/Irwin, 2012. Print.