The Collier Encyclopedia’s definition for probability is the concern for events that are not certain and the reasonableness of one expectation over another. These expectations are usually based on some facts about past events or what is known as statistics. Collier describes statistics to be the science of the classification and manipulation of data in order to draw inferences. Inferences here can be read to mean expectations, leading to the conclusion that the two go hand in hand in accomplishing what mankind has tried to accomplish since the beginning of time – predicting the future. It is the notion of science that this is the most accurate way to predict events yet to occur and this has lead to it being the most widely accepted “fortune telling'; tool in the world today.
Probability and Statistics most widespread use is in the arena of gambling. Gambling is big all over the world and lots of money is won and lost with their aid. In horse racing especially the statistics of a horse in terms of its physical condition and winning history sway numbers of persons into believing that the mathematical evidence that is derived can actually be a good indicator of a race’s outcome. Usually it is if the odds or probability are great in favor of the desired outcome. However the future is uncertain and races can turn out any of a number of different ways.
The field of medicine is another high subscriber to this forecasting technique. Potential diagnoses are frequently made based on a patient’s history or that of his ancestors and the calculated likelihood of him/her acquiring certain conditions. Statistics and probability aid in the decision making process of which test may be required for a given symptom and how a possible outbreak may be detected and contained. Strategies for isolating and dealing with diseases are often made with the aid of statistics on the percentage of a population that may have been infected and the probability of its escalation.
The weather forecasters use probability and statistics just as much if not more than any other field on earth. As weather patterns are not fully understood and are dynamic, analysts have to rely heavily on past weather systems and patterns to “guess'; or estimate the possibility of present weather systems to behave in similar manners. If the probability of its behavior, subject to certain factors, in one manner over another is high forecasters make decisions as to how to advise the public.
Bayes Theorem, allows you to combine two or more probabilities into a single number. To come up with a combined probability, multiply the initial probability by a single number which represents the “likelihood ratio”. That ratio will either inflate or deflate the original probability estimate. The Bayes Theorem allows you to update your predictions over time as new and ideally better information comes to
is based on actual events, which helps in showing the accuracy of the events. The
Epstein, Richard A. The Theory of Gambling and Statistical Logic. New York: Academic, 1977. Print.
Infectious diseases had major impacts and influences in the human history. Diseases such as Spanish Influenza or the Bubonic Plague have remarkable positions in history. Disease spread models are used to predict outcomes of an epidemic. These models are used to calculate the impact of an infectious disease, funding required for mass vaccinations and data for public health departments. The earliest mathematical model of infectious diseases was created by Daniel Bernoulli in 1766. This model was used to predict the outcome of inoculation against smallpox disease. In the modern world, these models are created using various software programs. The reason why I chose this subject is because I previously worked on some modelling simulations. Also my father is in the healthcare sector, so this topic looked very exciting to me. Predicting outcomes of infectious epidemics may save thousands of lives and millions of dollars. In the healthcare sector, accuracy and reliability is very important. In this project, the work function of the SIR epidemic model and some of its derivatives will be explored along with some theorems about this models. SIR model is the fundamental model of almost all modern epidemic models. SIR model is the most widely used disease spread model in the world. Also it is a simple epidemic model which has mathematics that commensurate with our class.
For people who are not statisticians, they may wonder what statisticians do, and how statistics could be applied in daily life. Statistics: A Guide to the Unknown is a supplementary reading materials designed for general readers even if he or she did not learn enough knowledge of statistics, mathematics and probability. Besides, it could give statisticians a general understanding of the important role of statistics in society. This book also analyzes how statistics assists people to gain useful information from massive data sets. In order to form a more respected book, the editors invite many distinguished researchers in statistics as authors. The book consists of twenty-five essays from different fields, including public policy and social science, science and technology, biology and medicine, business and industry, and hobbies and recreation. Each essay provides readers a description of how statistical methods are applied to solve issues in that field.
First we are going to talk about probability theory, which has to do with mathematics and analysis of random phenomena. You are probably used to putting the number of outcomes over the total amount of the object or total amount what you have. An example is, if you have a normal dice and you want the probability of rolling an odd number, you would take the total amount of odd numbers (3) and put that over the total (6) amount of numbers on the dice like so 3/6 which you can also reduce it to ½ because 3 is half of 6. This theory has been around since the sixteenth century and started off as the outcome you would get in a game, which was created by Pierre de Fermat, Blaise Pascal and Gerolamo Cardano. Later on in the seventeenth century Christiaan Huygens published a book on the subject.
A researcher determines that 42.7% of all downtown office buildings have ventilation problems. Is this a statistic or a parameter; explain your answer.
...e outcomes. Additional forecasts on what happens next will also support the scientific standard for prediction of future events.
Throughout the entire hurricane season, meteorologists keep a close watch on the Atlantic and the Pacific Oceans. They examine pictures of the area taken by satellites, and also take information on air pressure, wind speed, and temperatures. One of their most important jobs is to gather information on where the storm will hit, and how powerful it will be.
Although I, like many professional meteorologists, know that these comments are small jokes, it does bother me that the public, or at least a mass of the public hold a common perception that meteorologists just cannot be correct with their forecasts. Maybe I am getting too defensive, but listen to me when I say meteorologists have the burden to predict the unknown. It is not an easy task, nor is the countless hours of physics, calculus, differential equations, exponential mathematics, and chemistry easy to comprehend and learn. Meteorologists take their jobs very seriously as they are essentially the ‘spokesman’ for the weather and an elit...
Many theories of logic use mathematical terms to show how premises lead to conclusions. The Bayesian confirmation theory relates directly to probability. When applying this theory, a logician must know the probability of a given situation, have a conditional rule, and then he or she must apply the probability when the conditional rule is applied. This theory is used to determine an outcome based on a given condition. The probability of a given situation is x, when y occurs, or the probability is z if it does not occur. If y occurs, then the outcome of the given would be x. For example, if there is a high probability that a storm will occur if a given temperature drops and there is no temperature change, then it will most likely not rain because the temperature did not change (Strevens, 2012). By using observational data such as weather patterns, a person can arrive at a logical prediction or conclusion that will most likely come true based...
...xpected weather conditions over time, previous weather conditions, possible areas of less deteriorating weather conditions, expected duration of bad weather condition.
Forecasting is crucial in managing of any business; it enables the business to make decisions about purchases, production, raw material, costs and the price of a product and shipping. Forecasting enables a business to be proactive and plan for future demand instead of waiting for demand to emerge and then reacting to it, as this can cause a delay in customer orders. Demand forecast ensures faster order cycle times.
Probability is always surrounding us from stock markets to the ever-simple heads or tails. This very complicated area of mathematics can be explained in a simpler way. It is how likely an event is to happen. The probability of an event will always be between 0 and 1. The closer it is to one, the more likely the event is to happen.
For example biostatistics helps us to calculate age-adjusted cancer incidence rates to determine trends over time and locality, to compute statistical measures of the risk of developing brain tumors following cell phone use after adjusting for possible confounding variables, to quantify the relationship between