Want this question answered?
attiq
These bonds haven't identical length.
The average value of an a.c. voltage or current, over a complete cycle, is zero. For this reason, the average value is normally quoted over a half cycle and, for a sinusoidal waveform, is equal to 0.637 Vmax or 0.637 Imax.
form factor is defined as ratio between rms value and average value..
Average value is 8500 Kcal/cubic meter
A large value for the chi-squared statistic indicates that one should be suspiciuous of the null hypothesis, because the expected values and the observed values willdiffer by a large amount
The expected value is the average of a probability distribution. It is the value that can be expected to occur on the average, in the long run.
It is the test statistic.
When forming a hypothesis for quantitative research, a declarative hypothesis states the expected relation between variables, whereas a null hypothesis states that there is no significant relation.
A chi-square statistic can be large if either there is a large difference between the observed and expected values for one or more categories. However, it can also be large if the expected value in a category is very small. In the first case, it is likely that the data are not distributed according to the null hypothesis. In the second case, it can often mean that that, because of low expected values, adjacent categories need to be combined before the chi-square statistic is calculated.
A test statistic is a value calculated from a set of observations. A critical value depends on a null hypothesis about the distribution of the variable and the degree of certainty required from the test. Given a null hypothesis it may be possible to calculate the distribution of the test statistic. Then, given an alternative hypothesis, it is may be possible to calculate the probability of the test statistic taking the observed (or more extreme) value under the null hypothesis and the alternative. Finally, you need the degree of certainty required from the test and this will determine the value such that if the test statistic is more extreme than the critical value, it is unlikely that the observations are consistent with the hypothesis so it must be rejected in favour of the alternative hypothesis. It may not always be possible to calculate the distribution function for the variable.
sample statistic
A statistician may have some idea about some statistics in a data set, and there is a need to test whether or not that hypothesis is likely to be true. Data are collected and a test statistic is calculated. The value of this test statistic is used to determine the probability that the hypothesis is true.
The critical value is used to test a null hypothesis against an alternative hypothesis at some pre-defined level of significance. A test statistic is calculated from the outcomes of a set of trials and if this test statistic is more extreme than the critical value then the null hypothesis must be rejected in favour of the alternative.
You have not defined M, but I will consider it is a statistic of the sample. For an random sample, the expected value of a statistic, will be a closer approximation to the parameter value of the population as the sample size increases. In more mathematical language, the measures of dispersion (standard deviation or variance) from the calculated statistic are expected to decrease as the sample size increases.
The mean is the sum of all elements in the sequence divided by the total number of elements. It is a statistic which represents the expected value of any term in the sequence (the average value).
The expected value is the long-run average value of repetitions of the experiment it represents.