which of the following statements is true of statistical significance? course hero

Which is true about the relationship between statistical significance and clinical significance?

In clinical research, study results, which are statistically significant are often interpreted as being clinically important. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on clinical practice.

When the results are statistically significant this means?

Statistical significance refers to the claim that a result from data generated by testing or experimentation is likely to be attributable to a specific cause. A high degree of statistical significance indicates that an observed relationship is unlikely to be due to chance.

Which of the following statement is true about the null hypothesis?

Answer and Explanation: The option (c) is true. In hypothesis testing, the null hypothesis is true when two population proportion is assumed to be equal. Moreover, a study with a larger sample is equally likely compared to a smaller study to get the result P<0.05 .

How does sample size affect determinations of statistical significance?

Higher sample size allows the researcher to increase the significance level of the findings, since the confidence of the result are likely to increase with a higher sample size. This is to be expected because larger the sample size, the more accurately it is expected to mirror the behavior of the whole group.

What is an example of statistical significance?

Here's an example of that: A study found that a certain dietary supplement lowered the risk of getting a certain minor ailment from 2 in a 1000 (0.2%) down to 1 in a 1000 (0.1%). The sample size of the study was 30,000, so the difference between 0.2% and 0.1% is statistically significant (at 95% confidence).

How do you know if a test is statistically significant?

Interpret the value of t If the computed t-score equals or exceeds the value of t indicated in the table, then the researcher can conclude that there is a statistically significant probability that the relationship between the two variables exists and is not due to chance, and reject the null hypothesis.

Which one among the following statement is true in the context of the testing of hypothesis?

Answer. Answer: It is only alternative hypothesis that can be tested.

Which of the following statements are true with respect to hypothesis testing?

The correct option is C: The test statistic depends on the significance level. Explanation: Type 1 error occurs when the analyst rejects the null hypothesis, which is true, whereas the type 2 error occurs when the analyst accepts the null hypothesis, which is untrue.

Which is not type of test of significance for small samples Mcq?

The listing of the accessible population from which the sample isdrawn is called the………....Q.Which is not type of test of significance for small sample ?B.z-testC.F-testD.Q-testAnswer» d. Q-test1 more row

What is statistical significance in research?

In research, statistical significance is a measure of the probability of the null hypothesis being true compared to the acceptable level of uncertainty regarding the true answer.

Why is statistical significance important in research?

Why is Statistical Significance Important for Researchers? Statistical significance is important because it allows researchers to hold a degree of confidence that their findings are real, reliable, and not due to chance. But statistical significance is not equally important to all researchers in all situations.

What is the meaning of statistically significant difference?

A statistically significant difference is simply one where the measurement system (including sample size, measurement scale, etc.) was capable of detecting a difference (with a defined level of reliability). Just because a difference is detectable, doesn't make it important, or unlikely.

When the results are statistically significant This means quizlet?

Statistical significance means that the result observed in a sample is unusual when the null hypothesis is assumed to be true. When testing a hypothesis using the​ P-value Approach, if the​ P-value is​ large, reject the null hypothesis.

What does statistically significant mean in research?

In research, statistical significance is a measure of the probability of the null hypothesis being true compared to the acceptable level of uncertainty regarding the true answer.

What do we mean when we say that a result is statistically significant quizlet?

What do we mean when we say that a result is statistically significant? A result is statistically significant if it is unlikely to have occurred by chance. Results from a study of heart disease have statistical significance because heart disease is such an important health risks for adults.

Does statistically significant means reject null hypothesis?

A p-value less than 0.05 is typically considered to be statistically significant, in which case the null hypothesis should be rejected. A p-value greater than 0.05 means that deviation from the null hypothesis is not statistically significant, and the null hypothesis is not rejected.

What is the outcome of a hypothesis test?

denoted H0, (The outcome of a hypothesis test is "reject H0" or "fail to reject H0")

What is the probability of a statistic derived from a sample?

refers to the likelihood, or probability, that a statistic derived from a sample represents some genuine phenomenon in the population from which the sample was selected

What is the central limit theorem?

central limit theorem (CLT) states that, given certain conditions, the mean of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed. degrees of freedom.