The simple answer is no. This depends on a lot of factors such as alpha which determines the critical value and the absolute value of the difference between the claim and sample data. Mathematically speaking, all things being equal, the larger the sample size the larger the absolute value of the test statistic. The formula for the test statistic mean with sigma known is shown below. You can substitute values in and perform the mathematics. The larger the sample size, the larger the Z value; but note if the numerator is small, even a small denominator will not produce a large Z value. In fact, the numerator could be zero which would make the test statistic zero. Z = (Xbar - μxbar)/(σ/√n) (formula from Elementary Statistics by Mario F. Triola)
To start with you select your hypothesis and its opposite: the null and alternative hypotheses. You select a confidence level (alpha %), which is the probability that your testing procedure rejects the null hypothesis when, if fact, it is true.Next you select a test statistic and calculate its probability distribution under the two hypotheses. You then find the possible values of the test statistic which, if the null hypothesis were true, would only occur alpha % of the times. This is called the critical region.Carry out the trial and collect data. Calculate the value of the test statistic. If it lies in the critical region then you reject the null hypothesis and go with the alternative hypothesis. If the test statistic does not lie in the critical region then you have no evidence to reject the null hypothesis.
The answer depends on the underlying variance (standard deviation) in the population, the size of the sample and the procedure used to select the sample.
simple random sampling method
It is called convenience sampling.
The chief aim is to find a representative sample; that is, a sample which reflects the properties of the population, as a whole.
To start with you select your hypothesis and its opposite: the null and alternative hypotheses. You select a confidence level (alpha %), which is the probability that your testing procedure rejects the null hypothesis when, if fact, it is true.Next you select a test statistic and calculate its probability distribution under the two hypotheses. You then find the possible values of the test statistic which, if the null hypothesis were true, would only occur alpha % of the times. This is called the critical region.Carry out the trial and collect data. Calculate the value of the test statistic. If it lies in the critical region then you reject the null hypothesis and go with the alternative hypothesis. If the test statistic does not lie in the critical region then you have no evidence to reject the null hypothesis.
Select the transaction, then click the Reject button
Select the transaction, then click the Reject button
to select a random sample you pick them at random
Null hypotheses state that there is no relationship between select variables. For example, there is no relationship between personality and alcoholism.
It depends on the what the sample is for, but at least get both girls and boys in the sample.
no
The answer depends on the underlying variance (standard deviation) in the population, the size of the sample and the procedure used to select the sample.
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simple random sampling method
It is called convenience sampling.
The chief aim is to find a representative sample; that is, a sample which reflects the properties of the population, as a whole.