Science · Evidence and explanation

1943 paper; invented eight-value datasets

Luria and Delbrück’s 1943 Study: Why Fluctuations Matter

Use the 1943 resistance paper and two invented datasets to compare means and variances, distinguish models of variation, and avoid inferring a mutation rate.

Two invented lists with equal averages, different descriptive variances and an explicitly stated divisor.
2 and 2
Equal means in the invented lists
14.75 /2.25
Descriptive variances, dividing by 8
Not inferred
A biological mutation rate

The short answer

Two lists can have the same average while telling different stories about variation. Follow the historical question, then calculate an original example before deciding what its numbers do—and do not—establish.

Compare the quantities

Keep the claim within the model

These comparisons separate supplied assumptions, calculated results and missing evidence.

Teaching quantities are invented unless explicitly identified as historical.
Record or testWhat followsWhat remains separate
Dataset ATotal 16; mean 2; variance 14.75A historical measurement or fitted rate
Dataset BTotal 16; mean 2; variance 2.25Proof of a named probability distribution
Equal averagesOne shared summary statisticIdentical observations or biological causes

Chronology

A timeline of the turning points

  1. Paper published

    The source compares mechanisms and predicted variation.

  2. Original classroom datasets

    Neither list is a historical experimental table.

  3. Report the inference boundary

    A descriptive variance is not a mutation-rate estimate.

A surviving population did not settle the mechanism

The 1943 paper contrasts pre-exposure change with acquired-immunity explanations. Its footnote credits theory to Delbrück and experiments to Luria.

For the exercise below, compare the information retained by a mean with the information lost when the individual observations are discarded.

Sources for this section: [1]

Two invented lists with the same total

Use dataset A: [0,0,0,0,1,1,2,12] and dataset B: [0,0,1,2,2,3,4,4]. These eight-value lists are wholly invented; they do not reproduce a historical table. Each totals 16, so each mean is 16÷8=2.

An average therefore cannot distinguish these supplied lists. A report giving only the mean would hide the large value in A and the more even spread in B. Preserving individual observations is essential to the question being asked; a single summary can discard the feature that matters.

Sources for this section: [1]

Calculate the stated variance convention

Use descriptive population variance for the eight listed values:sum the squared differences from the mean, then divide by 8. In A the sum is 118, giving 14.75. In B it is 18, giving 2.25. A sample-variance calculation dividing by 7 would answer a different numerical question.

Worked answer: both means are 2, but the specified variances differ. The calculations show why equal means need not imply equal variability. They do not establish that either tiny invented list follows a particular probability distribution, and they do not yield a biological mutation rate.

Sources for this section: [1]

Connect a model to the interpretation

The paper contrasts independent pre-exposure change with random survival after exposure. The comparison concerns those models, rather than every form of genetic change.

Our toy lists illustrate the importance of retaining variation; they do not independently reproduce the historical test. To compare biological explanations, one would need justified assumptions, comparable conditions and sufficient observations. Other sources of heterogeneity could also affect a distribution, so a large descriptive variance is not a self-sufficient causal verdict.

Sources for this section: [1]

Exercise: repair an overconfident conclusion

An invented report says, “Both means are 2, so the mechanisms must be identical.” A second says, “A has the larger variance, so its exact mutation rate is now known.” Explain the separate errors without collecting or inventing more data.

Reference answer: the first discards differences in the supplied observations; the second converts a descriptive calculation into an unsupported parameter estimate. The better conclusion reports the mean, the variance convention and the limits of the inference. The historical biographies then supply the collaboration and research setting that a bare dataset cannot contain.

Sources for this section: [1] · [2]

Continue the chronology

Biography context

Explore United States through connected lives

Connected biographies

Scientists connected with this question

United StatesCulture

1912–1991

Salvador Luria

Microbiologist and scientific institution builderSalvador Luria studied bacterial viruses, helped establish microbial genetics and later combined research leadership at MIT with public political engagement.Read biography
United StatesCulture

1906–1981

Max Delbrück

Physicist and molecular biologistMax Delbrück moved from theoretical physics to biology, helping make viruses and fungi experimental systems for questions about heredity and response.Read biography

Quick answers

Common questions

Were the two eight-value lists used in 1943?
No. They are invented teaching data.
Can their variance reveal a mutation rate?
No. The exercise supplies neither an appropriate fitted model nor the biological information required.

Primary and institutional sources

How this history was checked

Read the specified original or institutional records alongside the explicitly invented teaching model; their different evidential roles are stated in the text. This article was reviewed on 29 October 2026.

  1. S.E.Luria and M.Delbrück; Genetics 28,491–511,1943; institutional PDF copyMutations of Bacteria from Virus Sensitivity to Virus Resistance
  2. U.S. National Library of Medicine Technical BulletinLuria papers:2005 institutional collection introduction