Related Experiment Video
Updated: Jan 1, 2026

09:32
Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
Published on: November 20, 2017
9.7K
No Association between 2D:4D Ratio and Hunting Success among Hadza Hunters
1Department of Anthropology, Durham University, Durham, DH1 3LE, UK. duncanstibs@cantab.net.
Human Nature (Hawthorne, N.Y.)
|December 16, 2019
Summary
The study found no link between finger length ratios (2D:4D ratio) and hunting skills in Tanzanian Hadza men. This challenges previous theories suggesting a connection between prenatal androgen exposure and athletic or hunting abilities.
Area of Science:
- Evolutionary Anthropology
- Human Biology
- Behavioral Ecology
Background:
- The 2D:4D ratio, or digit ratio, is linked to prenatal androgen exposure, with men typically having lower ratios than women.
- Previous research suggests an inverse relationship between 2D:4D ratio and athletic ability, and theorizes a similar link to hunting skills in hunter-gatherer populations.
- Existing studies have not directly tested this hypothesis in actual hunter-gatherer groups using ecologically valid measures of hunting success.
Purpose of the Study:
- To investigate the relationship between the 2D:4D ratio and hunting ability among the Tanzanian Hadza hunter-gatherers.
- To assess hunting reputation and specific hunting skills using a novel, granular assessment method.
Main Methods:
- Assessed the 2D:4D ratio in Tanzanian Hadza men.
- Employed a new method to evaluate hunting reputation, allowing for detailed differentiation among hunters.
- Measured two key hunting skills to provide ecologically valid indicators of hunting performance.
Main Results:
- No statistically significant relationship was found between the 2D:4D ratio and hunting reputation.
- The digit ratio did not correlate significantly with the two assessed hunting skills.
- Hadza men exhibited higher mean 2D:4D ratios compared to men in many Western populations.
Conclusions:
- The study provides no empirical support for the hypothesized negative correlation between 2D:4D ratio and hunting skill in this hunter-gatherer population.
- The findings suggest that the 2D:4D ratio may not be a reliable predictor of hunting ability or success.
- Alternative explanations, such as allometric scaling, are considered for the observed digit ratios.
Related Concept Videos
Odds Ratio
1.4K
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
1.4K
Testing a Claim about Population Proportion
3.8K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.8K
Testing a Claim about Mean: Unknown Population SD
5.3K
A complete procedure of testing a hypothesis about a population mean when the population standard deviation is unknown is explained here.
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
5.3K
Wald-Wolfowitz Runs Test II
494
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
494
Hazard Ratio
529
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
529
Two-Way ANOVA
3.3K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.3K

