Increasing alpha from .01 to .05 will increase the probability of rejecting the null hypothesis when it is true.
The p value for rejecting an hypothesis is more closely related to the type of errors and their consequences. The p value is not determined by the chi square - or any other - test but by the impact of the decision made on the basis of the test. The two types of errors to be considered are: what is the probability that you reject the null hypothesis when it is actually true (type I error), and what is the probability that you accept the null hypothesis when, in fact, it is false (type I error).. Reducing one type of error increase the other and there is a balance to be struck between the two. This balance will be influenced by the costs associated with making the wrong error. In real life, the effects (costs/benefits) of decisions are very asymmetrical.
When you increase the number of trials of an aleatory experiment, the experimental probability that is based on the number of trials will approach the theoretical probability.
motility
Type II errors are the case of false negatives. In hypothesis testing, we begin with a speculative hypothesis. A type 2 error is created when the test fails to reject the null hypothesis, when the alternative hypothesis is, in reality, true. The null hypothesis can be thought of as the status quo, and the alternative hypothesis is what our experiment is telling us. You can reduce type 2 errors by increasing alpha. However, by increasing alpha, type 1 errors increase, that is to fail to accept the null hypothesis, when the alternative is, in reality, false. Is there any way to reduce both errors? If you increase your sample size (of course with good data), for the same alpha, both will decrease. The understanding of this is very important. It happens with mad cow disease. The tests were very good at identifying that a healthy cow was, in fact,a healthy cow. In thousands of tests, they never had an error. So type 1 errors never occurred, but they had so few cases of sick cows, that it was hard to know if type 2 errors, a cow was sick, but the test showed healthy, ever occurred.
You improve your model through a better understanding of the underlying processes. Although more trials will improve the accuracy of experimental probability they will make no difference to the theoretical probability.
a small standard error and a large alpha level
When you increase correlation, you are increasing the probability of having very large losses, as well as the probability of having no loss at all. So, you are increasing the probability that senior tranches might experience significant losses but also the probability that the equity tranche is left untouched. As a consequance the spread on the latter decreases.
The p value for rejecting an hypothesis is more closely related to the type of errors and their consequences. The p value is not determined by the chi square - or any other - test but by the impact of the decision made on the basis of the test. The two types of errors to be considered are: what is the probability that you reject the null hypothesis when it is actually true (type I error), and what is the probability that you accept the null hypothesis when, in fact, it is false (type I error).. Reducing one type of error increase the other and there is a balance to be struck between the two. This balance will be influenced by the costs associated with making the wrong error. In real life, the effects (costs/benefits) of decisions are very asymmetrical.
When you increase the number of trials of an aleatory experiment, the experimental probability that is based on the number of trials will approach the theoretical probability.
- the speed of reaction increase with increasing temperature - the actual efficiency increase with increasing temperature
No. Increasing is a verb form, and a noun form (gerund). The adverb is "increasingly."
The probability increases.The probability increases.The probability increases.The probability increases.
Yes.
Yes, increasing your span of recognition can increase your reading rate.
Repetition.
Increasing the temperature of gas the volume increase.
Hypothesis: Will the speed of the parachute increase when more weight is put in to it and will it go slower if less weight is put in