Among agronomists, there appears to be a confusion in selecting among standard deviation (SD), standard error (SE) and confidence interval (CI) in reporting their results as figures and graphs. If there is a confusion in selection among them, there should also be difficulties in interpreting results published in peer-reviewed journals. This review paper aims to help researchers better suited for reporting their results as well as interpreting others by revisiting the definition of SD, SE and CI and explaining in plain words the concepts behind the formula. A variation among observation obtained from an experiment can be explained by the use of SD, a descriptive statistic. If one wants to draw an attention to a variation observed among plant germplasm collected from different regions or countries, SD can be reported along with the mean so that readers can get an idea how much variation exists in the particular set of germplasm. When the purpose of reporting experiment results is about inferring true mean of the population, it is advised to use SE or CI, both inferential statistics. For example, a certain chemical compound is to be quantified from plant materials, estimated mean with SD does not tell the range where the true mean content of the chemical compound would lie. It merely indicates how variable the measured values were from replications. In this case, it would be better to report the mean with SE or CI. The author recommends the use of CI over SE since CI is a sort of adjusted SE. The adjustment comes from t value that considers not only the probability but also n size.

서 언
 본 론
  표준편차 (Standard Deviation, SD)
  표준오차 (Standard Error, SE)
  신뢰구간(Confidence Interval, CI)
 적 용
 결 론
 적 요
 사 사
 REFERENCES

• 소윤섭(충북대학교 농업생명환경대학 식물자원학과) | Yoon-Sup So Corresponding author