It is the result of the experiment. It is the value of the observation.
The observation is more than 250 standard deviations (SD) away from the mean. For a normal distribution, the probability of being more than 3 SD from the mean is 0.0027 so the probability of an observation being 250 SD from the mean is infinitesimally small.
The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis.
It could refer to four standard errors. If an observation from a Gaussian (normal) distribution is 4 standard errors away from the mean, it has an extremely low probability.
The probability is 0.The probability is 0.The probability is 0.The probability is 0.
It is the result of the experiment. It is the value of the observation.
It means that there is a probability of 0.0968 that an observation as extreme as this occurred purely by chance.
You need a null hypothesis first. You then calculate the probability of the observation under the conditions specified by the null hypothesis.
Empirical means by observation, so empirical probability, or experimental probability, is the probability that is observed in a set of trials. For example, if you flip a coin ten times and get seven heads, your empirical probability is 7 in 10. This is different than the theoretical probability, which for a fair coin is 5 in 10, but that result will only be approximated by the empirical results, and then only with a larger number of trials.
The observation is more than 250 standard deviations (SD) away from the mean. For a normal distribution, the probability of being more than 3 SD from the mean is 0.0027 so the probability of an observation being 250 SD from the mean is infinitesimally small.
The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis.
For a continuous variable it is 0.5 but for a discrete variable the answer depends on the probability of the variable taking the mean value. It is half of the rest of the probability. If the discrete variable X has mean m and Prob(X = m) is p then Prob(X > m) = (1 - p)/2.
It could refer to four standard errors. If an observation from a Gaussian (normal) distribution is 4 standard errors away from the mean, it has an extremely low probability.
A posterior probability is the probability of assigning observations to groups given the data. A prior probability is the probability that an observation will fall into a group before you collect the data. For example, if you are classifying the buyers of a specific car, you might already know that 60% of purchasers are male and 40% are female. If you know or can estimate these probabilities, a discriminant analysis can use these prior probabilities in calculating the posterior probabilities. When you don't specify prior probabilities, Minitab assumes that the groups are equally likely.
In all probability - yes. In actually observation, then no. The chances are high, but our current technology doesn't allow us to determine individual stars let alone planets.
a quatitive observation is a observation that you can look at
The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.