Expected Error Rate Statistics
Contents |
proportion of samples that would fall between 0, 1, 2, and 3 standard deviations above and below the actual value. The standard error (SE) is the standard deviation of the sampling distribution of a statistic,[1] most expected error rate naive bayes commonly of the mean. The term may also be used to refer to an estimate expected error rate definition of that standard deviation, derived from a particular sample used to compute the estimate. For example, the sample mean is the
Error Rate Statistics Sample Size
usual estimator of a population mean. However, different samples drawn from that same population would in general have different values of the sample mean, so there is a distribution of sampled means (with its own mean
Human Error Rate Statistics
and variance). The standard error of the mean (SEM) (i.e., of using the sample mean as a method of estimating the population mean) is the standard deviation of those sample means over all possible samples (of a given size) drawn from the population. Secondly, the standard error of the mean can refer to an estimate of that standard deviation, computed from the sample of data being analyzed at the time. In statistical error rate calculator regression analysis, the term "standard error" is also used in the phrase standard error of the regression to mean the ordinary least squares estimate of the standard deviation of the underlying errors.[2][3] Contents 1 Introduction to the standard error 1.1 Standard error of the mean 1.1.1 Sampling from a distribution with a large standard deviation 1.1.2 Sampling from a distribution with a small standard deviation 1.1.3 Larger sample sizes give smaller standard errors 1.1.4 Using a sample to estimate the standard error 2 Standard error of the mean 3 Student approximation when σ value is unknown 4 Assumptions and usage 4.1 Standard error of mean versus standard deviation 5 Correction for finite population 6 Correction for correlation in the sample 7 Relative standard error 8 See also 9 References Introduction to the standard error[edit] The standard error is a quantitative measure of uncertainty. Consider the following scenarios. Scenario 1. For an upcoming national election, 2000 voters are chosen at random and asked if they will vote for candidate A or candidate B. Of the 2000 voters, 1040 (52%) state that they will vote for candidate A. The researchers report that candidate A is expected to receive 52% of the final vote, with a margin of error of 2%. In this scenario, the
- 25 Evaluation of sample results 26 - 32 Analysis of errors in the sample 27 - 30 Inferences to be drawn for the
Deviation Rate
population as a whole 31 - 32 Compliance with International Standards on Auditing 33 tolerable error definition Effective date 34 Appendix - Table 1 : Examples of factors influencing sample sizes for tests of control Table upper deviation rate definition 2 : Examples of factors influencing sample sizes for substantive procedures [7.97 (Supp. 4/97)] STATEMENT OF AUDITING STANDARDS 430 AUDIT SAMPLING (Issued July 1997) [7.97 (Supp. 4/97)] Statements of Auditing Standards (SASs) https://en.wikipedia.org/wiki/Standard_error are to be read in the light of SAS 010 "The scope and authority of auditing pronouncements". In particular, they contain basic principles and essential procedures (auditing standards), indicated by paragraphs in bold italic type, with which auditors are expected to comply in the conduct of any audit including those of companies applying section 141D of the Companies Ordinance. SASs also include explanatory and other material http://app1.hkicpa.org.hk/professionaltechnical/pronouncements/handbook/volume3a/sas430.htm which is designed to assist auditors in interpreting and applying auditing standards. Introduction 1. The purpose of this Statement of Auditing Standards (SAS) is to establish standards and provide guidance on the design and selection of an audit sample and the evaluation of the sample results. This SAS applies equally to both statistical and non-statistical sampling methods. Either method, when properly applied, can provide appropriate audit evidence. 2. When using either statistical or non-statistical sampling methods, auditors should design and select an audit sample, perform audit procedures thereon and evaluate sample results so as to provide sufficient appropriate audit evidence. (SAS 430.1) 3. "Audit sampling" means the application of audit procedures to less than 100% of the items within an account balance or class of transactions to enable auditors to obtain and evaluate audit evidence about some characteristic of the items selected in order to form or assist in forming a conclusion concerning the population. Audit sampling can be used as part of a test of control or as part of a substantive procedure. 4. It is important to recognise that certain testing procedures do not come within the definition of sampling. Test
faq • rss Community Log In Sign Up Add New Post Question: How are expected error rates calculated? 0 15 months ago by Andrew • 30 Canada Andrew • 30 wrote: I want to find the overall expected error rate of https://www.biostars.org/p/150886/ reads in a BAM file, as well as the expected number of errors. Currently for each base in a read, I find the ASCII value (number) of the quality (column 11), subtract 33, and remove the phred scale, which to my understanding would give me the probability that the base is wrong. I do this for every base in every read and sum the values up, and divide it by the total number of bases for all reads. error rate Is this correct? If not how would I calculate the expected error rate? bam expected error rate • 595 views ADD COMMENT • link • Not following Follow via messages Follow via email Do not follow written 15 months ago by Andrew • 30 1 That's correct, although note that a bam file can have multiple alignments for each read. ADD REPLY • link written 15 months ago by Brian Bushnell ♦ 6.5k Please log in to add expected error rate an answer. Similar posts • Search » How Are Sequencing Error Rates Defined? Frequently one hears about Illumina's error rate being 0.8% or thereabouts. How is this error rat... Expected Mutation Rate Matrix In an attempt to identify new subfamilies I would like to use the matrix that is the basis of PAM... filtering out the genes in RNA-seq experiment Hi Guys I have a set of RNA-seq data and so far I have prepared my data and the number of raw rea... Substitution error rate and indel error rate from BAM file I want to determine the substitution error rate and the indel error rate for a given BAM file. I... How To Calculate Over-Representation Of Tfbs Of Single Tf Per Gene I am now trying to locate single specific transcription factor binding site to over 100kb sequenc... Using Rate4Site To Calculate Mutation Rate Per Gene? I would like to calculate the mutation rate per gene based on an MSA. In this past post (C: Muta... E-values calculation (MEME) I'm trying to understand how MEME's E-values are calculated but can't find how could I reproduce ... InsideDNA: Benchmarking seven most popular genome assemblers Introduction: metrics for genome assembly comparison Several factors influence performance of de ... Does FPKM scale incorrectly in case of unequal mapping rates? I have the impression that FPKM as calculated by cufflinks doesn't correctly normalize for librar... Pr