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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.

03

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

Testing Hypotheses. In Exercises 13โ€“24, assume that a simple random sample has been selected and test the given claim. Unless specified by your instructor, use either the P-value method or the critical value method for testing hypotheses. Identify the null and alternative hypotheses, test statistic, P-value (or range of P-values), or critical value(s), and state the final conclusion that addresses the original claim.

Speed Dating Data Set 18 โ€œSpeed Datingโ€ in Appendix B includes โ€œattractiveโ€ ratings of male dates made by the female dates. The summary statistics are n = 199, x = 6.19, s = 1.99. Use a 0.01 significance level to test the claim that the population mean of such ratings is less than 7.00.

In Exercises 9โ€“12, refer to the exercise identified. Make subjective estimates to decide whether results are significantly low or significantly high, then state a conclusion about the original claim. For example, if the claim is that a coin favours heads and sample results consist of 11 heads in 20 flips, conclude that there is not sufficient evidence to support the claim that the coin favours heads (because it is easy to get 11 heads in 20 flips by chance with a fair coin).

Exercise 8 โ€œPulse Ratesโ€

P-Values. In Exercises 17โ€“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 ฮฑ = 0.05, should we reject H0or should we fail to reject H0?

The test statistic of z = 2.01 is obtained when testing the claim that pโ‰ 0.345.

Testing Claims About Proportions. In Exercises 9โ€“32, test the given claim. Identify the null hypothesis, alternative hypothesis, test statistic, P-value, or critical value(s), then state the conclusion about the null hypothesis, as well as the final conclusion that addresses the original claim. Use the P-value method unless your instructor specifies otherwise. Use the normal distribution as an approximation to the binomial distribution, as described in Part 1 of this section.

Touch Therapy Repeat the preceding exercise using a 0.01 significance level. Does the conclusion change?

In Exercises 13โ€“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.)

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