True or False: 1. Statistical significance is proof that the relationship was no

Question

True or False:

1. Statistical significance is proof that the relationship was not caused by weaknesses of the research design. T/F

2. Statistical significance is proof that the relationship is necessarily a strong one. T/F

3. Statistical significance is proof that the relationship is a valuable, meaningful, or previously unknown one. T/F

4. Statistical significance is proof that the relationship absolutely could not have been produced by sampling error. T/F

5. Statistical significance is proof that the variables are related as strongly within the population from which the sample was drawn (or are related at all). T/F

Explanation / Answer

It's important to understand, the merely having a low P-value and hence having a statistically significant set of variables just tells you that a sigificant relation exists. Nothing more.

With that being said, lets's get to the questions:

1) Statistical significance is proof that the relationship was not caused by weaknesses of the research design. - False.

Statistical significance is a parameter. The only inference that can be made out of it is the fact that the significance exists. Research Design cannot be inferred by the P value or significance. It depends on other additional factors as well.

2) Statistical significance is proof that the relationship is necessarily a strong one. False.

Significance is a statistical term that tells how sure you are that a difference or relationship exists. To say that a significant difference or relationship exists only tells half the story. We might be very sure that a relationship exists, but is it a strong, moderate, or weak relationship? After finding a significant relationship, it is important to evaluate its strength. Significant relationships can be strong or weak. Significant differences can be large or small. It just depends on your sample size.

3) Statistical significance is proof that the relationship is a valuable, meaningful, or previously unknown one. - False

When a statistic is significant, it simply means that you are very sure that the statistic is reliable. It doesn't mean the finding is important or that it has any decision-making utility.

4) Statistical significance is proof that the relationship absolutely could not have been produced by sampling error. - False

Same as point 2 and 1

5) Statistical significance is proof that the variables are related as strongly within the population from which the sample was drawn (or are related at all).

False

Statistical significance depends on sample size. This may or may not be true for the population. We can assume with a fair bit of certainity that the populations is related as well, but to deduce that the correlations would be as strong as the one in the sample is incorrect.

Related Questions

Navigate

• Browse (All)
• Browse T
• Subjects

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.