On the application of confidence limits to biostratigraphy: an example from diatoms

2020 ◽  
Author(s):  
Cristina Lopes ◽  
João Velez
Keyword(s):  
Sedimentation Rate ◽  
Confidence Level ◽  
Confidence Limits ◽  
Confidence Levels ◽  
Expedition 346 ◽  
Age Model

<p>For years, diatom-based biostratigraphy has been settings bio-events based on a qualitatively approach. This means that the biostratigraphy would set an age based on the findings or not of a certain species. However, how many species are needed to consider a certain datum as certain? One, ten, 100? Moreover, each biostratigrapher sets its on limits. One might consider one as enough and another 10. Therefore, the scale more often used is the absent, rare, frequent, common, dominant or abundant with an explanation of what of these definitions mean. This is very common in, for example, IODP expeditions.</p><p>However, what would happen to these biostratigraphy levels if one would apply, for example, a concept of 95% confidence level? Moreover, what would happen to an age model if this concept would be applied to all the biostratigraphy microfossil?</p><p>Here we will show Expedition 346 age model differences with and without confidence levels applied to diatoms. The differences can be significant and even considering the existence of a hiatus can be reconsider if confidence limits are applied, turning a possible hiatus into a very slow sedimentation rate having serious implications to the initial paleoceanographic interpretations.</p>

scholarly journals The internship dentists self confidence levels during root canal treatment procedures

2017 ◽  
Vol 5 (2) ◽  
pp. 121
Author(s):  
Mazen Doumani ◽  
Adnan Habib ◽  
Abrar Alhababi ◽  
Ahmad Bashnakli ◽  
Enass Shamsy ◽  
...  
Keyword(s):  
Confidence Level ◽  
Root Canal ◽  
Scoring System ◽  
Dental School ◽  
Root Canal Treatment ◽  
Confidence Levels ◽  
Self Confidence ◽  
Treatment Procedures

Self-confidence level assessment in newly graduated students is very important to evaluate the undergraduate endodontic courses. Objective: The aim of this study was to get information from internship dentists in Alfarabi dental college related to their confidence levels during root canal treatment procedures.Methods: Anonymous survey forms were sent to 150 internship dentists in Alfarbi dental college. They were asked to indicate their self-confidence level by Lickert’s scoring system ranging between 1 and 5.Results: Removal of broken instruments was determined as a procedure that was not experienced by 25.2% of the dentists. (44.6%) of dentists felt confident about taking radiographs during root canal treatment. 1.9 % of them reported as having very little confidence during retreatment. The irrigation was a procedure in which they felt very confident about (59.2%).Conclusion: The non-practiced endodontic procedure was clearly related to levels of self confidence among internship dentists; this means; a lot of studies in dental school should be performed to determine the weakness points or gaps in undergraduate endodontic courses.

Comparison of the 87 Rb → 87 Sr ages of the red granite of the Bushveld complex from measurements on the total rock and separated mineral fractions

1958 ◽  
Vol 245 (1240) ◽  
pp. 112-117 ◽  
Keyword(s):  
Confidence Level ◽  
Bushveld Complex ◽  
Crushed Rock ◽  
Confidence Limits ◽  
Single Determination ◽  
The Mean ◽  
Age Determinations

Age determinations on a portion of the total crushed rock, and on the felspar fraction of each of four widely separated samples of the red granite from the Bushveld complex are reported. A single determination from the separated biotite of one sample was made. These nine determinations lead to a mean age of 2.41 x 10 9 years [ t 1/2 = 6.3 x 10 10 years] or 1.92 x 10 9 years [ t 1/2 = 5.0 x 10 10 years]. There are no variations between individual determinations that are significant at the 99% confidence level. For the unweighted mean age the 99% confidence limits are ± 0.13 x 10 9 years. Despite the low enrichment of 87 Sr the ‘total rock ’ method shows 99% confidence limits of ± 0.22 x 10 9 years for the mean of four determinations.

MULTIVARIATE MODELS AND VARIABILITY INTERVALS: A LOCAL RANDOM SET APPROACH

2011 ◽  
Vol 19 (05) ◽  
pp. 799-823 ◽  
Author(s):  
THOMAS FETZ
Keyword(s):  
Confidence Level ◽  
Structural Mechanics ◽  
Random Sets ◽  
Confidence Limits ◽  
Random Set ◽  
Multivariate Functions ◽  
Multivariate Models ◽  
Multivariate Case ◽  
Fréchet Bounds

This article is devoted to the propagation of families of variability intervals through multivariate functions comprising the semantics of confidence limits. At fixed confidence level, local random sets are defined whose aggregation admits the calculation of upper probabilities of events. In the multivariate case, a number of ways of combination is highlighted to encompass independence and unknown interaction using random set independence and Fréchet bounds. For all cases we derive formulas for the corresponding upper probabilities and elaborate how they relate. An example from structural mechanics is used to exemplify the method.

Statistical Considerations for Determining Extent of Piping Inspections for RBI or API-570 Driven Inspections

2002 ◽  
Author(s):  
D. Hobbs ◽  
A. P.-D. Ku
Keyword(s):  
Random Field ◽  
Confidence Level ◽  
Confidence Limits ◽  
Damage State ◽  
Statistical Tools ◽  
Process Piping ◽  
Piping Systems ◽  
Inspection Data ◽  
Engineering Practices

This paper outlines a method for calculating the number of inspection locations for process piping inspections. The method determines the number of piping inspection locations required for an inspection to detect a particular damage state within the confidence limits of the premised inspection’s reliability. It is intended to be used for piping inspections per API-570, “Piping Inspection Code” and in the application of risk-based inspection concepts presented in AP1-581, “Risk Based Inspection, Base Resource Document”. This method combines recognized inspection and piping engineering practices and random-field statistical tools to calculate the number of inspection locations in piping systems with probabilistic confidence level. This method has provisions for future applications when inspection data is known, or there is greater uncertainty in the distribution of the degradation or the reliability of the inspection data is different than those premised in this paper.

On Determination of Sample Size to Evaluate Reliability Growth Plans

2011 ◽  
Author(s):  
X. Jin ◽  
P. Woytowitz ◽  
T. Tan
Keyword(s):  
Sample Size ◽  
Confidence Level ◽  
Semiconductor Manufacturing ◽  
Field Performance ◽  
Reliability Growth ◽  
Confidence Levels ◽  
Equipment Reliability ◽  
Margin Of Error ◽  
Reliability Performance

The reliability performance of Semiconductor Manufacturing Equipments (SME) is very important for both equipment manufacturers and customers. However, the response variables are random in nature and can significantly change due to many factors. In order to track the equipment reliability performance with certain confidence, this paper proposes an efficient methodology to calculate the number of samples needed to measure the reliability performance of the SME tools. This paper presents a frequency-based Statistics methodology to calculate the number of sampled tools to evaluate the SME reliability field performance based on certain confidence levels and error margins. One example case has been investigated to demonstrate the method. We demonstrate that the multiple weeks accumulated average reliability metrics of multiple tools do not equal the average of the multiple weeks accumulated average reliability metrics of these tools. We show how the number of required sampled tools increases when the reliability performance is improved and quantify the larger number of sampled tools required when a tighter margin of error or higher confidence level is needed.

scholarly journals Study on the Confidence and Reliability of the Mean Seismic Probability Risk Model

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Xiao-Lei Wang ◽  
Da-Gang Lu
Keyword(s):  
Seismic Design ◽  
Confidence Level ◽  
Risk Model ◽  
Safety Evaluation ◽  
Design Parameters ◽  
Critical Infrastructures ◽  
High Confidence ◽  
Confidence Levels ◽  
The Mean ◽  
Mean Risk

The mean seismic probability risk model has widely been used in seismic design and safety evaluation of critical infrastructures. In this paper, the confidence levels analysis and error equations derivation of the mean seismic probability risk model are conducted. It has been found that the confidence levels and error values of the mean seismic probability risk model are changed for different sites and that the confidence levels are low and the error values are large for most sites. Meanwhile, the confidence levels of ASCE/SEI 43-05 design parameters are analyzed and the error equation of achieved performance probabilities based on ASCE/SEI 43-05 is also obtained. It is found that the confidence levels for design results obtained using ASCE/SEI 43-05 criteria are not high, which are less than 95%, while the high confidence level of the uniform risk could not be achieved using ASCE/SEI 43-05 criteria and the error values between risk model with target confidence level and mean risk model using ASCE/SEI 43-05 criteria are large for some sites. It is suggested that the seismic risk model considering high confidence levels instead of the mean seismic probability risk model should be used in the future.

scholarly journals An analytical method of estimating Value-at-Risk on the Belgrade Stock Exchange

2009 ◽  
Vol 54 (183) ◽  
pp. 119-138 ◽  
Author(s):  
Milica Obadovic ◽  
Mirjana Obadovic
Keyword(s):  
At Risk ◽  
Failure Rate ◽  
Confidence Level ◽  
Analytical Method ◽  
Value At Risk ◽  
Risk Evaluation ◽  
Risk Model ◽  
Stock Exchange ◽  
Confidence Levels ◽  
The Given

This paper presents market risk evaluation for a portfolio consisting of shares that are continuously traded on the Belgrade Stock Exchange, by applying the Value-at-Risk model - the analytical method. It describes the manner of analytical method application and compares the results obtained by implementing this method at different confidence levels. Method verification was carried out on the basis of the failure rate that demonstrated the confidence level for which this method was acceptable in view of the given conditions.

scholarly journals Cosmic Ray Anisotropy above 1015 eV

1987 ◽  
Vol 40 (3) ◽  
pp. 423 ◽  
Author(s):  
RW Clay
Keyword(s):  
Internal Consistency ◽  
Confidence Level ◽  
Cosmic Ray ◽  
Published Data ◽  
High Confidence ◽  
Real Effect ◽  
Confidence Levels ◽  
High Confidence Level

An examination is made of published data on cosmic ray anisotropy at energies above about 1015 eV. Both amplitude and phase results are examined in an attempt to assess the confidence which can be placed in the observations as a whole. It is found that whilst many published results individually may suggest quite high confidence levels of real measured anisotropy, the data taken as a whole are less convincing. Some internal consistency in the phase results suggests that a real effect may have been measured but, again, this is not at a high confidence level.

scholarly journals A SEGMENT-BASED APPROACH FOR DTM DERIVATION OF AIRBORNE LIDAR DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 115-120
Author(s):  
Dejin Tang ◽  
Xiaoming Zhou ◽  
Jie Jiang ◽  
Caiping Li
Keyword(s):  
Confidence Level ◽  
Spatial Location ◽  
Point Clouds ◽  
Airborne Lidar ◽  
High Confidence ◽  
Confidence Levels ◽  
Segment Distribution ◽  
Adjacent Segments ◽  
Airborne Lidar Data ◽  
High Confidence Level

With the characteristics of LIDAR system, raw point clouds represent both terrain and non-terrain surface. In order to generate DTM, the paper introduces one improved filtering method based on the segment-based algorithms. The method generates segments by clustering points based on surface fitting and uses topological and geometric properties for classification. In the process, three major steps are involved. First, the whole datasets is split into several small overlapping tiles. For each tile, by removing wall and vegetation points, accurate segments are found. The segments from all tiles are assigned unique segment number. In the following step, topological descriptions for the segment distribution pattern and height jump between adjacent segments are identified in each tile. Based on the topology and geometry, segment-based filtering algorithm is performed for classification in each tile. Then, based on the spatial location of the segment in one tile, two confidence levels are assigned to the classified segments. The segments with low confidence level are because of losing geometric or topological information in one tile. Thus, a combination algorithm is generated to detect corresponding parts of incomplete segment from multiple tiles. Then another classification algorithm is performed for these segments. The result of these segments will have high confidence level. After that, all the segments in one tile have high confidence level of classification result. The final DTM will add all the terrain segments and avoid duplicate points. At the last of the paper, the experiment show the filtering result and be compared with the other classical filtering methods, the analysis proves the method has advantage in the precision of DTM. But because of the complicated algorithms, the processing speed is little slower, that is the future improvement which should been researched.

scholarly journals Determination of the Uncertainties in S-Curve Logistic Fits

2022 ◽  
Author(s):  
THEODORE MODIS
Keyword(s):  
General Result ◽  
Confidence Level ◽  
Simulated Data ◽  
Historical Period ◽  
Confidence Levels ◽  
Minimization Technique ◽  
Data Points ◽  
S Curve ◽  
Better Than

Look-up tables and graphs are provided for determining the uncertainties during logistic fits, on the three parameters M, α and to describing an S-curve of the form: S(t) = M/(1+exp(-α(t-t0))).The uncertainties and the associated confidence levels are given as a function of the uncertainty on the data points and the length of the historical period. Correlations between these variables are also examined; they make “what-if” games possible even before doing the fit.The study is based on some 35,000 S-curve fits on simulated data covering a variety of conditions and carried out via a χ2 minimization technique. A rule-of-thumb general result is that, given at least half of the S-curve range and a precision of better than 10% on each historical point, the uncertainty on M will be less than 20% with 90% confidence level.

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