Related Concept Videos
00:59Uncertainty: Overview
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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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01:04Random Error
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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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01:10Propagation of Uncertainty from Systematic Error
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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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00:59Propagation of Uncertainty from Random Error
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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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00:54Uncertainty: Confidence Intervals
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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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01:19Autism Spectrum Disorder
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Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
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Autistic Heterogeneity: Linking Uncertainties and Indeterminacies.
1School of Sociology and Social Policy, University of Leeds, UK.
Science As Culture
|May 19, 2017
Summary
Scientists navigate uncertainty in autism research by discussing epistemological and ontological uncertainties, alongside autism's inherent heterogeneity. This dialogue helps understand autism and scientific uncertainty more broadly.
Area of Science:
- Neurodevelopmental disorders
- Philosophy of science
- Scientific methodology
Background:
- Autism is characterized by significant uncertainty, posing challenges for scientific understanding.
- Scientists grapple with reconciling diverse research methods and taxonomic coherence in autism.
Purpose of the Study:
- To explore how scientists discuss uncertainty and indeterminacy in autism research.
- To analyze the interplay between epistemological, ontological uncertainties, and autism's heterogeneity.
Main Methods:
- Qualitative analysis of scientific discourse on autism.
- Examination of how scientists conceptualize and communicate uncertainty.
Main Results:
- Autism research involves epistemological uncertainties (methodological diversity) and ontological uncertainties (taxonomic coherence issues).
- Autism's inherent heterogeneity, termed indeterminacy, is discussed in both inter-personal (between individuals) and intra-personal (within individuals) forms.
- Scientists intertwine concepts of uncertainty and indeterminacy, blurring strict epistemic-ontic boundaries.
Conclusions:
- Understanding the dialogue around uncertainty and indeterminacy is crucial for comprehending autism and its heterogeneity.
- This analysis offers insights into 'uncertainty work' within scientific research more generally.