Spike Train Decoding
... where N1 is the number of spikes before the transition time, T 12 and N2 is the number of spikes after T12 and before t. 5) Continue with the new firing rate, calculating the probability of the set of ISIs beginning from the transition point. Notes: this could be improved by incorporating realistic ...
... where N1 is the number of spikes before the transition time, T 12 and N2 is the number of spikes after T12 and before t. 5) Continue with the new firing rate, calculating the probability of the set of ISIs beginning from the transition point. Notes: this could be improved by incorporating realistic ...
Optimization and Control: Examples Sheet 1
... estimate of the number of prior evaluations of F needed to find F (d0 , d1 , . . . , dn ). 2. A deck of cards is thoroughly shuffled and placed face down on the table. You turn over cards one by one, counting the numbers of reds and blacks you have seen so far. Exactly once, whenever you choose, you ...
... estimate of the number of prior evaluations of F needed to find F (d0 , d1 , . . . , dn ). 2. A deck of cards is thoroughly shuffled and placed face down on the table. You turn over cards one by one, counting the numbers of reds and blacks you have seen so far. Exactly once, whenever you choose, you ...
Basic mathematical concepts from probability and information theory.
... Consider now a subsystem on the timescale mentioned above. Clearly many different microscopic configurations could occur and would be consistent with the assumed density %. Consider a large number of such microscopic configurations. Such a group is commonly referred to as a statistical ensemble. The ...
... Consider now a subsystem on the timescale mentioned above. Clearly many different microscopic configurations could occur and would be consistent with the assumed density %. Consider a large number of such microscopic configurations. Such a group is commonly referred to as a statistical ensemble. The ...
1 Statistics Aneta Siemiginowska a chapter for “X-ray Astronomy Handbook”
... of the scientific analysis and answer this question. Statistic allows us to take decisions in Science, evaluate observations, models, formulate questions and proceed forward with investigations. The statistic is needed at every step of our scientific analysis. Statistic is a quantity that summarized ...
... of the scientific analysis and answer this question. Statistic allows us to take decisions in Science, evaluate observations, models, formulate questions and proceed forward with investigations. The statistic is needed at every step of our scientific analysis. Statistic is a quantity that summarized ...
Probabilities in Science
... theorem (named after Thomas Bayes, a 19th century British scholar interested in probability): Since Pr(p) * Pr(q/p) = Pr(q) * Pr(p/q), then (dividing through by Pr(q) & reversing the order): Bayes: Pr (p/q) = Pr (p) * Pr(q/p) / Pr(q) This is an important result because it says something about how we ...
... theorem (named after Thomas Bayes, a 19th century British scholar interested in probability): Since Pr(p) * Pr(q/p) = Pr(q) * Pr(p/q), then (dividing through by Pr(q) & reversing the order): Bayes: Pr (p/q) = Pr (p) * Pr(q/p) / Pr(q) This is an important result because it says something about how we ...
Second unit of Q520: More Probability
... σ for various values of x in a table. Usually a table would only list values between 0 and around 3. This is because the negatives come for free by symmetry, and 99.7% of the probability is within three standard deviations of the mean. If you keep in mind the picture of the bell curve, you’ll unders ...
... σ for various values of x in a table. Usually a table would only list values between 0 and around 3. This is because the negatives come for free by symmetry, and 99.7% of the probability is within three standard deviations of the mean. If you keep in mind the picture of the bell curve, you’ll unders ...
Acid Rain
... For 98% of such intervals, the sample mean would not differ from the actual population mean by more than ___.107____ e) What does the interval suggest about the year-2000 pH of rain in the area in comparison with the pH level in 1990? Be very specific in your explanation. Since the interval is com ...
... For 98% of such intervals, the sample mean would not differ from the actual population mean by more than ___.107____ e) What does the interval suggest about the year-2000 pH of rain in the area in comparison with the pH level in 1990? Be very specific in your explanation. Since the interval is com ...
Probability box
),steps=500.png?width=300)
A probability box (or p-box) is a characterization of an uncertain number consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed. Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes.An example p-box is shown in the figure at right for an uncertain number x consisting of a left (upper) bound and a right (lower) bound on the probability distribution for x. The bounds are coincident for values of x below 0 and above 24. The bounds may have almost any shapes, including step functions, so long as they are monotonically increasing and do not cross each other. A p-box is used to express simultaneously incertitude (epistemic uncertainty), which is represented by the breadth between the left and right edges of the p-box, and variability (aleatory uncertainty), which is represented by the overall slant of the p-box.