1005L- PRE-TEST FOR WORKSHOP ON RESEARCH PROBLEMS AND RESEARCH QUESTIONS

1. The following statements are true about statistical questions and conclusions

1. Substantive questions are framed as statistical questions for analysis
2. Statistical conclusions may differ from substantive conclusions because of bias
3. Statistical significance is exactly the same as clinical or practical significance
4. Some substantive questions cannot be answered statistically
5. A valid substantive conclusion can be from an invalid statistical conclusion

2. The following statements are true about statistical questions and conclusions

1. Bio-statistics always conclusively answers substantive questions
2. Substantive conclusions require interpretation
3. Statistical inference is mostly deductive
4. A statistical question is framed to be answered quantitatively
5. Data is not necessary in formulating a statistical conclusion

3. The following statements are true about hypotheses and the scientific methods

1. Hypothesis formulation is done only after carrying out the experiment
2. Informal use of hypotheses in science is not acceptable
3. Scientists should be open minded when generating hypotheses
4. A hypothesis is a belief that can be supported but not contradicted by experiments
5. Rejection of a hypothesis affects the credibility of the scientist who suggested it

4. The following statements are true about hypotheses and the scientific method

A.      Use of a priori beliefs in the interpretation of experimental studies is unscientific

B.      Use of intuition has no role in the interpretation of experimental studies

C.      Anecdotal observations are reliable scientific evidence

D.      Some phenomena in the universe can not be tested scientifically

E.       Empirical investigation is not the only source of knowledge

F.       No valid scientific experiment can be carried out without a hypothesis

5. The following statements are true about the null and alternative hypotheses

1. H₀ states that there is no difference between the two comparison groups
2. H₀ assumes that apparent differences between groups are due to sampling error.
3. H_A disagrees with H₀
4. H₀ and H_A are complimentary
5. H₀ and H_A are exhaustive and between them cover all the possibilities.
6. A hypothesis can be proved beyond all reasonable doubt

6. The following statements are true about the null and alternative hypotheses

1. H₀ assumes that there are biological difference between compared groups
2. H_A assumes that apparent biological differences are due to sampling error.
3. H₀ can be accepted if the evidence is overwhelmingly in its favor
4. Scientific hypotheses can never be proved in a conclusive and final way
5. Hypothesis testing is not considered part of the scientific method

7. The following statements are true about the null and alternative hypotheses

A.     In obvious cases, there is no need to state H₀ and H_A before the experiment

B.     H₀ and H_A should always be stated together

C.     H₀ may be accepted if the sample size is large enough

D.     If H₀ is rejected, H_A is automatically proved

E.      Only 1 valid experiment is necessary to prove/disprove a hypothesis

8. The following statements are true about a statistically significant test

A.     H₀ is false

_B.        H₀ is not rejected

C.     Observations are not compatible with H₀

D.     Observed differences are due to sampling variation

E.      Observations may be or may not be real/true biological phenomena.

9. The following statements are true about a statistically non significant test

A.     H₀ is not false

B.     H₀ is true

C.     H₀ is not rejected

D.     Observations are compatible with H₀

E.      Observations are due to sampling variation or random errors of measurement

F.      Observations are artificial, apparent and not real biological phenomena.

10. The following statements are true about the interpretation of hypothesis tests

A.     A statistically significant may have no clinical significance

B.     A statistically significant may have no clinical importance

C.     A statistically significant may have no practical significance

D.     A statistically significant may have no practical importance

E.      Confounding and wrong measurements can lead to misleading statistical significance

F.      Clinically important differences may not be statistically significant for small samples

11. The following statements are true about the interpretation of hypothesis tests

A.     Statistical significance implies practical or clinical significance

B.      Statistical significance could be clinically insignificant

C.     Clinically significant findings may not reach statistical significance

D.     Prior experience is needed in interpreting clinical significance of hypothesis testing

E.      The level of significance used depends on the type of study