Discuss the difference between statistical significance and practical significance.

Short Answer

Expert verified

The differences between both statistical significance and practical significance are found through the specified significance level.

Step by step solution

01

Step 1. Given Information

Two terms statistical significance and practical significance are given.

02

Step 2. Stating the difference

Result of a hypothetical test is significant or statistical significant if the null hypothesis is rejected at any specified significance level.
Statistical significance means that on a specified significant level, the data provides suffice information to conclude that the actual truth is different from the truth stated in the null hypothesis.

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Step 3. Stating the difference

It may happen that the result of a hypothesis test is significant for a significance level but is insignificant for another significance level (a result of a hypothesis test will be insignificant if we specify the significance level smaller than the P-value of that test).

So, it is clear that statistical significance of any truth(i.e. of same hypothesis) may be different from practical significance of that truth.

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Most popular questions from this chapter

In Exercises 1–4, use these results from a USA Today survey in which 510 people chose to respond to this question that was posted on the USA Today website: “Should Americans replace passwords with biometric security (fingerprints, etc)?” Among the respondents, 53% said “yes.” We want to test the claim that more than half of the population believes that passwords should be replaced with biometric security.

Number and Proportion

a. Identify the actual number of respondents who answered “yes.”

b. Identify the sample proportion and the symbol used to represent it.

P-Values. In Exercises 17–20, do the following:

a. Identify the hypothesis test as being two-tailed, left-tailed, or right-tailed.

b. Find the P-value. (See Figure 8-3 on page 364.)

c. Using a significance level of = 0.05, should we reject H0or should we fail to reject H0?

The test statistic of z = -1.94 is obtained when testing the claim that p=38 .

In Exercises 13–16, refer to the exercise identified and find the value of the test statistic. (Refer to Table 8-2 on page 362 to select the correct expression for evaluating the test statistic.)

Exercise 6 “Cell Phone”

In Exercises 1–4, use these results from a USA Today survey in which 510 people chose to respond to this question that was posted on the USA Today website: “Should Americans replace passwords with biometric security (fingerprints, etc)?” Among the respondents, 53% said “yes.” We want to test the claim that more than half of the population believes that passwords should be replaced with biometric security.

Requirements and Conclusions

a. Are any of the three requirements violated? Can the methods of this section be used to test the claim?

b. It was stated that we can easily remember how to interpret P-values with this: “If the P is low, the null must go.” What does this mean?

c. Another memory trick commonly used is this: “If the P is high, the null will fly.” Given that a hypothesis test never results in a conclusion of proving or supporting a null hypothesis, how is this memory trick misleading?

d. Common significance levels are 0.01 and 0.05. Why would it be unwise to use a significance level with a number like 0.0483?

Identifying H0 and H1 . In Exercises 5–8, do the following:

a. Express the original claim in symbolic form.

b. Identify the null and alternative hypotheses.

Online Data Claim: Most adults would erase all of their personal information online if they could. A GFI Software survey of 565 randomly selected adults showed that 59% of them would erase all of their personal information online if they could.

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