# Assignment 3 case 7 2 carmakers target

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Apply networkstatistical, time-series, or causal models Model runs usually quick; model provides explainable logic for estimates; model may be improved over time Need models often difficult to construct ; requires providing model inputs; unknown unknowns may bias models The usual measure of the accuracy of an estimate is the absolute value of the difference between the estimate and the outcome [13].

Forecasting The Path of the Red River A forecast, according to my use of the word, describes potential future outcomes and probabilities. A confidence interval, which shows a range of possible outcome values and provides the estimated probability that the range will enclose the actual outcome, is often used to characterize the uncertainty in a forecast [14].

However, more information is provided by a probability distribution.

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For this reason, I like to think of a forecast as being a probability distribution for an uncertain future outcome. Producing only a single estimate for an uncertainty can seriously mislead decision makers. The flood occurred in May of the year and was caused by record snowfall followed by Assignment 3 case 7 2 carmakers target and unusually warm spring temperatures.

Weather Service predicted the rising Red River would crest at 49 feet. Accordingly, flood management plans were based on this figure.

In fact, the river crested above 50 feet, breaching dikes and unleashing floodwaters throughout the Red River Valley. In some areas water reached inland more than 3 miles from the river. An estimated 50, people were forced from their homes. Perhaps surprisingly, forecasters have been jailed for providing an estimate without probabilities.

In seven people engineers, scientists, and a civil servant were jailed in Italy following an earthquake in which people died. At their trial, it was alleged that they had failed in their duty by not properly assessing and communicating the risk that an earthquake was imminent.

Their offence was that they had simply conveyed the most likely outcome, no earthquake, rather than a probabilistic forecast that might have alerted people to the small chance of a strong earthquake [17]. The main methods used for forecasting are variations of the same methods listed in the table above for estimation.

Since forecasting methods that produce probabilities are most prominently used for risk assessmentdetailed descriptions of methods are provided in Part 5: Misestimating Likelihoods Although providing probabilities is important, probability estimates are often biased. People find uncertain situations particularly difficult to think about.

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Studies show that people make systematic errors when estimating how likely uncertain events are. And, outcomes that are quite unlikely are typically estimated to be more probable than they are. Furthermore, people often behave as if extremely unlikely, but still possible outcomes have no chance whatsoever of occurring [18].

People systematically over- or under-estimate probabilities. In addition to systematically misestimating low and high probabilities, studies show that people consistently misestimate the likelihoods of events with certain characteristics.

For example, having viewed television coverage of the collapse of the pedestrian bridge at Florida International University, a construction project manager might be inclined to increase safety inspections and purchase additional insurance.

Recency bias relates to the tendency to attribute more salience to recent stimuli or observations, which can lead to the overestimation of the likelihood that an unlikely event that occurred recently will soon reoccur [9]. For example, an IT risk manager who experienced a server failure on a prior project will likely assess a higher probability of a server failure on a current project.

Hindsight bias, also known as the I knew-it-all-along bias, refers to the inclination, after some rare event has occurred, to see the event as having been predictable, despite there having been little or no objective basis for predicting it. Representativeness bias refers to the tendency to judge the probability of a hypothesis by considering how much the hypothesis resembles that with which they are familiar.

For example, some therapists diagnose most of their patients with multiple personality disorder, while other therapists never see a case of multiple personality disorder in their entire career. Illusion of control bias refers to the tendency of people to believe they can control the probabilities of events when in fact they cannot [20].

For example, in the game of craps, a player may throw the dice softly for low numbers and hard for high numbers [21]. For example, though sports fans may believe players shoot successfully in streaks the hot hand theoryan analysis of data showed that, if anything, success on a previous throw very slightly increases the probability of a miss on a subsequent throw [23].

Other major biases and errors that distort estimates and forecasts are described in greater detail below. Overconfidence Overconfidence has been called, "perhaps the most robust finding in the psychology of judgment" [24].

We believe we are more accurate at making estimates than we are. Apparently, most of us prefer being precisely wrong rather than vaguely right. For example, British mathematician Lord Kelvin said, "Heavier-than-air flying machines are impossible.A forecast, according to my use of the word, describes potential future outcomes and probabilities.

A confidence interval, which shows a range of possible outcome values and provides the estimated probability that the range will enclose the actual outcome, is . As a follow-up to Tuesday’s post about the majority-minority public schools in Oslo, the following brief account reports the latest statistics on the cultural enrichment of schools in Austria.

Vienna is the most fully enriched location, and seems to be in roughly the same situation as Oslo. Many thanks to Hermes for the translation from skybox2008.com As we approach yet another debt ceiling and require an additional \$1 trillion just to keep the system afloat, we urge our readers to consider the distinct possibility that we remain on the brink, and are closer than ever before to a total breakdown in the financial, economic and social stability of the world.

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McKinsey Global Institute Our mission is to help leaders in multiple sectors develop a deeper understanding of the global economy. As we approach yet another debt ceiling and require an additional \$1 trillion just to keep the system afloat, we urge our readers to consider the distinct possibility that we remain on the brink, and are closer than ever before to a total breakdown in the financial, economic and social stability of the world.

By Patrick Coughlin. Effective structural fire protection requires that fire departments quickly respond to fires with enough resources to .

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