Probability Clause Samples

Probability. Decisions or predictions are often based on data—numbers in context. These decisions or predictions would be easy if the data always sent a clear message, but the message is often obscured by variability. Statistics provides tools for describing variability in data and for making informed decisions that take it into account. Data are gathered, displayed, summarized, examined, and interpreted to discover patterns and deviations from patterns. Quantitative data can be described in terms of key characteristics: measures of shape, center, and spread. The shape of a data distribution might be described as symmetric, skewed, flat, or ▇▇▇▇ shaped, and it might be summarized by a statistic measuring center (such as mean or median) and a statistic measuring spread (such as standard deviation or interquartile range). Different distributions can be compared numerically using these statistics or compared visually using plots. Knowledge of center and spread are not enough to describe a distribution. Which statistics to compare, which plots to use, and what the results of a comparison might mean, depend on the question to be investigated and the real-life actions to be taken. Randomization has two important uses in drawing statistical conclusions. First, collecting data from a random sample of a population makes it possible to draw valid conclusions about the whole population, taking variability into account. Second, randomly assigning individuals to different treatments allows a fair comparison of the effectiveness of those treatments. A statistically significant outcome is one that is unlikely to be due to chance alone, and this can be evaluated only under the condition of randomness. The conditions under which data are collected are important in drawing conclusions from the data; in critically reviewing uses of statistics in public media and other reports, it is important to consider the study design, how the data were gathered, and the analyses employed as well as the data summaries and the conclusions drawn. Random processes can be described mathematically by using a probability model: a list or description of the possible outcomes (the sample space), each of which is assigned a probability. In situations such as flipping a coin, rolling a number cube, or drawing a card, it might be reasonable to assume various outcomes are equally likely. In a probability model, sample points represent outcomes and combine to make up events; probabilities of events can be computed...

Probability. The distinguisher returns 1 if it guesses that it is interacting with the real world oracle and returns 0 otherwise. makes 3 2n/2 construction queries, 3 2n/2 primitive queries to π1, and 3 2n/2 primitive query to π2 in total and operates as follows.

Probability. The probability of the risk being realized (becoming an issue) is assessed using a scale of 1 through 5: 1 – Remote; 2 – Unlikely; 3 – Possible; 4 – Likely; 5 – Certain. If the risk is already an issue, this probability is set to 5.

Probability. Specifically, probability of the underlying property market moving around. Remember, by selling you a 1 month call option on his house, the house seller is exposing himself to the risk of the underlying property market changing. If there is a property crash, we will not choose to buy the house and the house seller will be left with an unsold house that has reduced in value. And if there is a sharp rise in property prices, the house seller will not be able to take advantage of the increased value of his house as we will exercise our right to buy at £100K. In summary, a significant change in the property market will cause the house seller either to lose money or to miss out on a profitable opportunity. In general then, all other things being equal, the greater the probability of the underlying market moving, the greater the option price.

Probability. STATUS – current status of the risk (typical values are “open” or “closed”) The following Risk Matrix will be used to establish the severity of risk: High (3) 3 6 9 Medium (2) 2 4 6 Low (1) 1 2 3 Low (1) Medium (2) High (3) Based on Subcontractor’s experience, the following have been identified as risks that could have negative effect on project timeline, cost and/or scope: RISK ID RISK NAME RISK DESCRIPTION PROB. IMPACT SEVERITY Mitigation 1 Environment not ready HW environment (servers) are not ready on time for the installation and configuration 3 3 9 Subcontractor can provide a temporary environment. This is not in the current scope and would require a change order 2 VPN ports not opened City does not open up the ports for ▇▇▇▇▇▇ personnel and for communication ▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇▇▇▇ ▇▇▇▇▇▇ ▇ ▇ ▇ ▇▇▇▇ ▇▇ should be engaged early. Subcontractor can provide additional consulting on this subject. This is not in the current scope and would require a change order 3 AMI not ready AMI is not ready on time, or is not sending the data 3 3 9 City to engage AMI vendor early in project and get commitments from vendor on timelines 4 Data source for Datasync not ready Data source (e.g. views, files) not ready for Datasync 3 3 9 City to engage CIS vendor early in project and get commitments from vendor on timelines. Alternatively, if City has the skillset, City can develop the views themselves. Throughout the duration of the project, as risks are identified they will be added to the Risk Log and will be reviewed at bi-weekly Status Meetings with the team to determine the possibility of occurrence and the best plan for mitigation. If identified risk(s) and/or mitigation strategies are deemed to have an effect on project timeline, or budget, or scope, Change Request may be created, as per section 5.3, to address those concerns.  Acceptance Management and Transition to Ongoing Support In general, once system testing has been completed, and the City staff has been trained on the system, the City staff will have the necessary tools to review and start using the system. City will have access to their own instance of the ▇▇▇▇▇▇ Software, loaded with customer data, to train and test on. During this time, the Subcontractor will continue to be responsive to the City and fix any outstanding lower severity issues discovered by system usage. The Subcontractor will also provide the City with documents to permit ongoing training on system use, operation, and system maintenance. Once t...

Probability. Specifically, the probability of a claim being made. This is directly related to the location of the property. Simply, the greater the probability of a claim, the greater the price of the insurance. As we will see at a later stage, broadly speaking, probability in the insurance world translates as volatility in the option world. Probability and volatility are closely related. As a general rule, all other things being equal, the greater the probability of a claim, the greater the option price.

Probability. Statistics

Probability. A global variable P is defined in the model. This variable is initialized at zero, and is decremented by the events.

Probability. These findings and procedures will be reported formally and it is the aim of the involved stakeholders to make the GUI available to other researchers and country programs in the ten loa co-endemic countries in Africa (Angola, Cameroon, Central African Republic, Chad, Congo, Democratic Republic of Congo, Equatorial Guinea, Nigeria, South Sudan, and Uganda). As global health networks and intervention methods grow in complexity, it is vital to ensure that communication lines between the multifarious stakeholders remain transparent and accessible. Moreover, financial costs for NTD control will likely remain constricted, and this GUI will ideally lead toward more cost-effective decision-making and management for co- endemic regions of LF/oncho and loa by limiting treating to a minimum while preserving safety. The programming of this particular tool aims to provide health policymakers with a statistically rigorous method of providing certainty in their decision-making, and the assurance of usability will hopefully play an important role in the goal to eliminate LF, oncho, and SAEs related to loiasis.