Confidence intervals and hypothesis tests
... Usually (but not always), the null hypothesis corresponds to a baseline or boring finding, and the alternative hypothesis corresponds to some interesting finding. Once we have the two hypotheses, we’ll use the data to test which hypothesis we should believe. “Significance” is usually defined in term ...
... Usually (but not always), the null hypothesis corresponds to a baseline or boring finding, and the alternative hypothesis corresponds to some interesting finding. Once we have the two hypotheses, we’ll use the data to test which hypothesis we should believe. “Significance” is usually defined in term ...
Diego#2
... A little Probability and Statistics Before testing a hypothesis, we must set up the hypothesis in a quantitative manner. The measurements done in epidemiological studies must be a number of some sort. (i.e. number of patients that did not receive a drug and died, mean blood pressure in HIV patients ...
... A little Probability and Statistics Before testing a hypothesis, we must set up the hypothesis in a quantitative manner. The measurements done in epidemiological studies must be a number of some sort. (i.e. number of patients that did not receive a drug and died, mean blood pressure in HIV patients ...
Quiz505
... In the following experiment we roll a fair die 5 times. a) What is the probability of the sequence “1,2,3,4,5”. P = (1/6)^5 (each number has P=1/6 and all numbers are independent. Alternatively: there is 1 way to achieve this and 6^5 ways in S). b) What is the probability that the sequence starts wi ...
... In the following experiment we roll a fair die 5 times. a) What is the probability of the sequence “1,2,3,4,5”. P = (1/6)^5 (each number has P=1/6 and all numbers are independent. Alternatively: there is 1 way to achieve this and 6^5 ways in S). b) What is the probability that the sequence starts wi ...
Lecture #9
... Consider a distribution D over space XY X - the instance space; Y - set of labels. (e.g. +/-1) Can think about the data generation process as governed by D(x), and the labeling process as governed by D(y|x), such that D(x,y)=D(x) D(y|x) This can be used to model both the case where labels are gener ...
... Consider a distribution D over space XY X - the instance space; Y - set of labels. (e.g. +/-1) Can think about the data generation process as governed by D(x), and the labeling process as governed by D(y|x), such that D(x,y)=D(x) D(y|x) This can be used to model both the case where labels are gener ...
How do I Test my Data for Normality? - Integral
... not discussed in this article. Here, we focus on the interpretation. If the p-value is “small” (usually less than 0.05), then we have strong evidence that the data is not normal (does not come from a normal distribution). If the p-value is “large” (usually more than 0.10), then we assume that the da ...
... not discussed in this article. Here, we focus on the interpretation. If the p-value is “small” (usually less than 0.05), then we have strong evidence that the data is not normal (does not come from a normal distribution). If the p-value is “large” (usually more than 0.10), then we assume that the da ...