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Regression How To Calculate Standard Error

the estimate from a scatter plot Compute the standard error of the estimate based on errors of prediction Compute the standard error using Pearson's correlation Estimate the standard error of the estimate based on a sample Figure 1 shows two regression examples. You can

Standard Error Of Regression Coefficient

see that in Graph A, the points are closer to the line than they are in standard error of estimate interpretation Graph B. Therefore, the predictions in Graph A are more accurate than in Graph B. Figure 1. Regressions differing in accuracy of prediction. standard error of the regression The standard error of the estimate is a measure of the accuracy of predictions. Recall that the regression line is the line that minimizes the sum of squared deviations of prediction (also called the sum of squares error).

Standard Error Of Regression Interpretation

The standard error of the estimate is closely related to this quantity and is defined below: where σest is the standard error of the estimate, Y is an actual score, Y' is a predicted score, and N is the number of pairs of scores. The numerator is the sum of squared differences between the actual scores and the predicted scores. Note the similarity of the formula for σest to the formula for σ.  It turns

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out that σest is the standard deviation of the errors of prediction (each Y - Y' is an error of prediction). Assume the data in Table 1 are the data from a population of five X, Y pairs. Table 1. Example data. X Y Y' Y-Y' (Y-Y')2 1.00 1.00 1.210 -0.210 0.044 2.00 2.00 1.635 0.365 0.133 3.00 1.30 2.060 -0.760 0.578 4.00 3.75 2.485 1.265 1.600 5.00 2.25 2.910 -0.660 0.436 Sum 15.00 10.30 10.30 0.000 2.791 The last column shows that the sum of the squared errors of prediction is 2.791. Therefore, the standard error of the estimate is There is a version of the formula for the standard error in terms of Pearson's correlation: where ρ is the population value of Pearson's correlation and SSY is For the data in Table 1, μy = 2.06, SSY = 4.597 and ρ= 0.6268. Therefore, which is the same value computed previously. Similar formulas are used when the standard error of the estimate is computed from a sample rather than a population. The only difference is that the denominator is N-2 rather than N. The reason N-2 is used rather than N-1 is that two parameters (the slope and the intercept) were estimated in order to estimate the sum of squares. Formulas for a sample comparable to the ones for a population

it comes to determining how well a linear model fits the data. However, I've stated previously that R-squared is overrated. Is there a different goodness-of-fit statistic that standard error of the slope can be more helpful? You bet! Today, I’ll highlight a sorely underappreciated

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regression statistic: S, or the standard error of the regression. S provides important information that R-squared does not. What is the standard error of the estimate is a measure of quizlet the Standard Error of the Regression (S)? S becomes smaller when the data points are closer to the line. In the regression output for Minitab statistical software, you can find S http://onlinestatbook.com/2/regression/accuracy.html in the Summary of Model section, right next to R-squared. Both statistics provide an overall measure of how well the model fits the data. S is known both as the standard error of the regression and as the standard error of the estimate. S represents the average distance that the observed values fall from the regression line. Conveniently, it tells you how wrong the http://blog.minitab.com/blog/adventures-in-statistics/regression-analysis-how-to-interpret-s-the-standard-error-of-the-regression regression model is on average using the units of the response variable. Smaller values are better because it indicates that the observations are closer to the fitted line. The fitted line plot shown above is from my post where I use BMI to predict body fat percentage. S is 3.53399, which tells us that the average distance of the data points from the fitted line is about 3.5% body fat. Unlike R-squared, you can use the standard error of the regression to assess the precision of the predictions. Approximately 95% of the observations should fall within plus/minus 2*standard error of the regression from the regression line, which is also a quick approximation of a 95% prediction interval. For the BMI example, about 95% of the observations should fall within plus/minus 7% of the fitted line, which is a close match for the prediction interval. Why I Like the Standard Error of the Regression (S) In many cases, I prefer the standard error of the regression over R-squared. I love the practical, intuitiveness of using the natural units of the response variable. And, if I need precise predictions, I can q

Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more http://stats.stackexchange.com/questions/85943/how-to-derive-the-standard-error-of-linear-regression-coefficient about Stack Overflow the company Business Learn more about hiring developers or posting ads http://www.okstate.edu/ag/agedcm4h/academic/aged5980a/5980/newpage24.htm with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer standard error The best answers are voted up and rise to the top How to derive the standard error of linear regression coefficient up vote 2 down vote favorite 3 For this univariate linear regression model $$y_i = \beta_0 + \beta_1x_i+\epsilon_i$$ given data set $D=\{(x_1,y_1),...,(x_n,y_n)\}$, the coefficient estimates are $$\hat\beta_1=\frac{\sum_ix_iy_i-n\bar x\bar y}{n\bar x^2-\sum_ix_i^2}$$ $$\hat\beta_0=\bar y - \hat\beta_1\bar x$$ Here is my question, according to the book and Wikipedia, the standard error of standard error of $\hat\beta_1$ is $$s_{\hat\beta_1}=\sqrt{\frac{\sum_i\hat\epsilon_i^2}{(n-2)\sum_i(x_i-\bar x)^2}}$$ How and why? standard-error inferential-statistics share|improve this question edited Mar 6 '15 at 14:38 Christoph Hanck 9,44832149 asked Feb 9 '14 at 9:11 loganecolss 50311026 stats.stackexchange.com/questions/44838/… –ocram Feb 9 '14 at 9:14 @ocram, thanks, but I'm not quite capable of handling matrix stuff, I'll try. –loganecolss Feb 9 '14 at 9:20 1 @ocram, I've already understand how it comes. But still a question: in my post, the standard error has $(n-2)$, where according to your answer, it doesn't, why? –loganecolss Feb 9 '14 at 9:40 add a comment| 1 Answer 1 active oldest votes up vote 7 down vote accepted 3rd comment above: I've already understand how it comes. But still a question: in my post, the standard error has (n−2), where according to your answer, it doesn't, why? In my post, it is found that $$ \widehat{\text{se}}(\hat{b}) = \sqrt{\frac{n \hat{\sigma}^2}{n\sum x_i^2 - (\sum x_i)^2}}. $$ The denominator can be written as $$ n \sum_i (x_i - \bar{x})^2 $$ Thus, $$ \widehat{\text{se}}(\hat{b}) = \sqrt{\frac{\hat{\sigma}^2}{\sum_i (x_i - \bar{x})^2}} $$ With $$ \hat{\sigma}^2 = \frac{1}{n-2} \sum_i \hat{\epsilon}_i^2 $$ i.e. the Mean Square Error (MSE) in the ANOVA table, we end up with your expression for $\widehat{\text{se}}(\hat{b})$. The $n-2$ term accounts fo

permission. MODULE S3 REGRESSION

A prediction of the levels of one variable when another is held constant at several levels. Based on average variation remaining constant over time due to the tendency in nature for extreme scores to move toward the mean. Used to predict for individuals on the basis of information gained from a previous sample of similar individuals. Regression Equation

= estimated y and is the value on the y axis across from the point on the regression line for the predictor x value. (Sometimes represented by or y.) This is the estimated value of the criterion variable given a value of the predictor variable. a = the intercept point of the regression line and the y axis. It is calculated through the equation ; therefore, the means of both variables in the sample and the value of b must be known before a can be calculated. b = the slope of the regression line and is calculated by this formula: If the Pearson Product Moment Correlation has been calculated, all the components of this equation are already known. x = an arbitrarily chosen value of the predictor variable for which the corresponding value of the criterion variable is desired. Example: A farmer wised to know how many bushels of corn would result from application of 20 pounds of nitrogen. The 20 pounds of nitrogen is the x or value of the predictor variable. The predicted bushels of corn would be y or the predicted value of the criterion variable.

Using the example we began in correlation: Pounds of Nitrogen (x) Bushels of Corn (y) x y 10 -40 1600 30 -20 400 800 20 -30 900 40 -10 100 300 50 0 0 50 0 0 0 70 20 400 60 10 100 200 100 50 2500 70 20 400 1000 250 0 5400 250 0 1000 2300 We calculate the components of the regression equation beginning with b. This gives us the slope of the regression line. For each 1.00 increment increase in x, we have a 0.43 increase in y. Next, we calculate a. We can now plot our regression graph and predict graphically from it. Or we can calculate the predicted values more accurately through the regression equation. If we wish to know how much more corn to expect from a 35 pound application of nitrogen, we calculate: Standard Error

The standard error for the estimate is calculated by the following formula: The formula may look formidable, but we already have calculated all of the components except

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Regression Average Error p deviation MSD of an estimator of a procedure for estimating an unobserved quantity measures the average of the squares of the errors or deviations that is the difference between the estimator and what is estimated MSE is a risk root mean square error interpretation function corresponding to the expected value of the squared error loss or quadratic loss The standard error of regression formula difference occurs because of randomness or because the estimator doesn't account for information that could produce a more accurate estimate The MSE p Standard Error Of The Regression p is a measure

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Relationship Between Standard Error And Variance p average squared deviation from the mean Variance in a population is x is a value from the population is the standard error formula mean of all x n is the number of x in the population p Standard Error Excel p is the summation Variance is usually estimated from a sample drawn from a population The unbiased estimate standard error regression of population variance calculated from a sample is xi is the ith observation from a sample of the population x-bar is the sample mean n sample size - is degrees of p

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Regression Standard Error p the estimate from a scatter plot Compute the standard error of the estimate based on errors of prediction Compute the standard error using Pearson's correlation Estimate the standard error of the estimate based on a sample Figure shows two p Standard Error Of Coefficient p regression examples You can see that in Graph A the points are closer to the standard error of regression formula line than they are in Graph B Therefore the predictions in Graph A are more accurate than in Graph B Figure standard error of regression interpretation Regressions differing in accuracy of

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Regression Standard Error Values p The standard error of the coefficient is always positive Use the standard error of the coefficient to measure the precision of the estimate of the standard error of coefficient coefficient The smaller the standard error the more precise the estimate how to calculate standard error of regression Dividing the coefficient by its standard error calculates a t-value If the p-value associated with this t-statistic standard error of the regression is less than your alpha level you conclude that the coefficient is significantly different from zero For example a materials engineer at a furniture manufacturing site

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Relationship Between Standard Error And Confidence Interval p DisclaimerPublic Health TextbookResearch Methods a - Epidemiology b - Statistical Methods c - Health Care Evaluation and Health Needs Assessment d - Qualitative MethodsDisease p Standard Error And Confidence Limits Worked Example p Causation and Diagnostic a - Epidemiological Paradigms b - Epidemiology of Diseases of calculate confidence interval from standard error in r Public Health Significance c - Diagnosis and Screening d - Genetics e - Health and Social Behaviour f - Environment g - p Error Interval Maths p Communicable Disease h - Principles and Practice of Health Promotion i

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Regression Standard Error Estimation p the estimate from a scatter plot Compute the standard error of the estimate based on errors of prediction Compute the standard error using Pearson's correlation Estimate the standard error of the estimate based on a sample Figure p Standard Error Of Coefficient p shows two regression examples You can see that in Graph A the standard error of estimate interpretation points are closer to the line than they are in Graph B Therefore the predictions in Graph A are more accurate p Standard Error Of The Regression p than in Graph B Figure Regressions differing

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Regression Parameter Standard Error p Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta standard error of coefficient multiple regression Discuss the workings and policies of this site About Us Learn p Standard Error Of Beta Hat p more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us p Standard Error Of Beta Coefficient Formula p Cross Validated Questions Tags Users Badges Unanswered Ask Question Cross Validated is a question and answer site for people interested in statistics machine learning data

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Relationship Between Mse And Standard Error Of Estimate p To Read This Book Notation Value-at-Risk Measures p Mean Square Error Example p Risk Measures Market Risk Value-at-Risk Risk mean absolute error Limits Other Applications of Value-at-Risk Examples Value-at-Risk Measures History of mean square error in r Value-at-Risk Further Reading Mathematical Preliminaries Motivation Mathematical Notation Gradient Gradient-Hessian Approx Ordinary Interpolation Complex Numbers p Sum Of Squared Errors p Eigenvalues and Eigenvectors Cholesky Factorization Minimizing a Quadratic Polynomial Ordinary Least Squares Cubic Spline Interpolation Finite Difference Approximations Newton s Method Change of Variables Formula Numerical Integration One Dim Numerical Integration Multi Dim

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Relationship Between Standard Error Of Estimate And R Squared p it comes to determining how well a linear model fits the data However I've stated previously that R-squared is overrated Is there a p Standard Error Of Estimate Formula p different goodness-of-fit statistic that can be more helpful You bet Today standard error of the regression I rsquo ll highlight a sorely underappreciated regression statistic S or the standard error of the regression S provides important p Standard Error Of Estimate Interpretation p information that R-squared does not What is the Standard Error of the Regression S S becomes smaller

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Relationship Between R Squared And Standard Error p using regression analysis ANOVA or design of experiments DOE you need to determine how well the model fits the data To help you out Minitab p Standard Error Of Regression Formula p statistical software presents a variety of goodness-of-fit statistics In this post we rsquo ll standard error of the regression explore the R-squared R statistic some of its limitations and uncover some surprises along the way For standard error of regression coefficient instance low R-squared values are not always bad and high R-squared values are not always good What Is Goodness-of-Fit

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Regression Standard Error Of The Estimate p the estimate from a scatter plot Compute the standard error of the estimate based on errors of prediction Compute the standard error using Pearson's correlation Estimate the standard error of the estimate based on a sample Figure shows two regression examples You standard error of estimate interpretation can see that in Graph A the points are closer to the line than they standard error of estimate calculator are in Graph B Therefore the predictions in Graph A are more accurate than in Graph B Figure Regressions differing in accuracy standard error of estimate

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Regression How To Calculate Standard Error Of Coefficients p Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more standard error of coefficient multiple regression about Stack Overflow the company Business Learn more about hiring developers or posting ads p Standard Error Of Beta Coefficient Formula p with us Cross Validated Questions Tags Users Badges Unanswered Ask Question Cross Validated is a question and answer site for standard error of regression coefficient excel people interested in statistics

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Regression Beta Standard Error Formula p For linear regression on a single variable see simple linear regression For the computation of least squares curve fits see numerical methods for linear least squares standard error of beta coefficient Part of a series on Statistics Regression analysis Models Linear regression Simple p Standard Error Of Coefficient In Linear Regression p regression Ordinary least squares Polynomial regression General linear model Generalized linear model Discrete choice Logistic regression Multinomial p Standard Error Of Beta Linear Regression p logit Mixed logit Probit Multinomial probit Ordered logit Ordered probit Poisson Multilevel model Fixed effects Random effects

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Regression Coefficient Standard Error Formula p Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might standard error of coefficient in linear regression have Meta Discuss the workings and policies of this site About standard error of coefficient multiple regression Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads standard deviation of regression coefficient with us Cross Validated Questions Tags Users Badges Unanswered Ask Question Cross Validated is a question and answer site for people interested in statistics machine learning data standard error

relation of standard deviation to standard error
Relation Of Standard Deviation To Standard Error p transformation standard errors must be of means calculated from within an intervention group and not standard errors of the difference standard error to standard deviation calculator in means computed between intervention groups Confidence intervals for means calculate standard error from standard deviation in excel can also be used to calculate standard deviations Again the following applies to confidence intervals for mean values p Convert Standard Deviation To Standard Error In Excel p calculated within an intervention group and not for estimates of differences between interventions for these see Section Most confidence intervals

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Regression What Is Standard Error p it comes to determining how well a linear model fits the data However I've stated previously that R-squared is overrated Is there a different goodness-of-fit statistic standard error of regression formula that can be more helpful You bet Today I rsquo ll highlight a sorely p Standard Error Of Regression Coefficient p underappreciated regression statistic S or the standard error of the regression S provides important information that R-squared does not p Standard Error Of Estimate Interpretation p What is the Standard Error of the Regression S S becomes smaller when the data points

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Relationship Between Reliability And Standard Error Of Measurement p than the score the student should actually have received true score The difference between the observed score and the true score is called the error score S standard error of measurement calculator true S observed S error In the examples to the right Student standard error of measurement and confidence interval A has an observed score of His true score is so the error score would be Student p Standard Error Of Measurement Interpretation p B has an observed score of His true score is so the error score would be

relationship between variance and standard error
Relationship Between Variance And Standard Error p average squared deviation from the mean Variance in a population is x is a value from the population is the p Standard Error Formula p mean of all x n is the number of x in the population standard error regression is the summation Variance is usually estimated from a sample drawn from a population The unbiased estimate standard error symbol of population variance calculated from a sample is xi is the ith observation from a sample of the population x-bar is the sample mean n sample size - is degrees of p

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Relationship Between Standard Error Estimate Correlation p the estimate from a scatter plot Compute the standard error of the estimate based on errors of prediction Compute the standard error using Pearson's correlation Estimate the standard error of the estimate based on standard error of correlation coefficient formula a sample Figure shows two regression examples You can see that in types of correlation pdf Graph A the points are closer to the line than they are in Graph B Therefore the predictions in Graph weak correlation A are more accurate than in Graph B Figure Regressions differing in accuracy of prediction

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Regression Standard Error Of Mean p proportion of samples that would fall between and standard deviations above and below the actual value The standard error SE is the standard deviation of the sampling distribution of a statistic most commonly of the mean The term may also be used p Standard Error Of Regression Formula p to refer to an estimate of that standard deviation derived from a particular sample used to standard error of regression coefficient compute the estimate For example the sample mean is the usual estimator of a population mean However different samples drawn from that same population

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Relationship Between Standard Error Of The Mean And Sample Size p describe the parameters of a population based on the description statistics of a set of elements drawn from the population In terms of the climate and attitudes survey that many of you were recently asked to complete we can describe the population sampling frame study population and sample What is the primary strength of using a the relationship between sample size and sampling error is quizlet probability sampling method First if many independent random samples are selected from a population the sample statistics purpose of sampling in research provided

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Relationship Between Sample Variance And Standard Error p average squared deviation from the mean Variance in a population is x is a value from the population is the p Standard Error Formula p mean of all x n is the number of x in the population standard error excel is the summation Variance is usually estimated from a sample drawn from a population The unbiased estimate p Standard Error Regression p of population variance calculated from a sample is xi is the ith observation from a sample of the population x-bar is the sample mean n sample size - is

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Relationship Between Standard Deviation And Standard Error Of Mean p Health Search databasePMCAll DatabasesAssemblyBioProjectBioSampleBioSystemsBooksClinVarCloneConserved DomainsdbGaPdbVarESTGeneGenomeGEO DataSetsGEO ProfilesGSSGTRHomoloGeneMedGenMeSHNCBI Web SiteNLM when to use standard deviation vs standard error CatalogNucleotideOMIMPMCPopSetProbeProteinProtein ClustersPubChem BioAssayPubChem CompoundPubChem SubstancePubMedPubMed HealthSNPSparcleSRAStructureTaxonomyToolKitToolKitAllToolKitBookToolKitBookghUniGeneSearch termSearch Advanced difference between standard error and standard deviation pdf Journal list Help Journal ListClin Orthop Relat Resv SepPMC Clin Orthop Relat difference between standard deviation and standard error formula Res Sep Published online May doi s - - - PMCID PMC In Brief Standard Deviation and Standard ErrorDavid J standard error of the mean excel Biau MD PhDDepartement de Biostatistique et Informatique Medicale H x f

relationship between standard deviation standard error
Relationship Between Standard Deviation Standard Error p transformation standard errors must be of means calculated from within an intervention group and not standard errors of the difference in means computed between intervention groups Confidence intervals calculate standard error from standard deviation in excel for means can also be used to calculate standard deviations Again the following p Convert Standard Deviation To Standard Error In Excel p applies to confidence intervals for mean values calculated within an intervention group and not for estimates of differences between interventions when to use standard deviation vs standard error for these see Section Most confidence

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Relative Standard Error Of The Mean p estimates for Labour Force data News Media Media Centre ABS in the Media ABS Statistics relative standard error excel Publications Release Dates Resources for Reporting Statistics Conferences Seminars and Events relative standard error proportion Contact Us Quick Links Consumer Price Index Unemployment Rate Retail Trade Figures Building Approvals Figures GDP standard error formula Trend Figures What is a Standard Error and Relative Standard Error Reliability of estimates for Labour Force data On this page Why do we have Standard Errors standard error vs standard deviation Importance of Standard Errors Standard Error versus Relative

relationship between standard deviation and standard error of the mean
Relationship Between Standard Deviation And Standard Error Of The Mean p Health Search databasePMCAll DatabasesAssemblyBioProjectBioSampleBioSystemsBooksClinVarCloneConserved DomainsdbGaPdbVarESTGeneGenomeGEO DataSetsGEO ProfilesGSSGTRHomoloGeneMedGenMeSHNCBI Web SiteNLM CatalogNucleotideOMIMPMCPopSetProbeProteinProtein ClustersPubChem BioAssayPubChem when to use standard deviation vs standard error CompoundPubChem SubstancePubMedPubMed HealthSNPSparcleSRAStructureTaxonomyToolKitToolKitAllToolKitBookToolKitBookghUniGeneSearch termSearch Advanced Journal list Help Journal standard error vs standard deviation example ListBMJv Oct PMC BMJ Oct doi bmj PMCID PMC Statistics standard error in excel NotesStandard deviations and standard errorsDouglas G Altman professor of statistics in medicine and J Martin Bland professor of health statistics Cancer Research p Standard Error In R p UK NHS Centre for Statistics in Medicine Wolfson College Oxford OX UD

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Relative Standard Deviation Error Bars p proportion of samples that would fall between and standard deviations above and below the actual value The standard error SE is the standard deviation of the sampling distribution of a p Standard Error Formula p statistic most commonly of the mean The term may also be used to refer standard error vs standard deviation to an estimate of that standard deviation derived from a particular sample used to compute the estimate For example the sample p Standard Error Calculator p mean is the usual estimator of a population mean However different samples drawn from

relationship between standard error and deviation
Relationship Between Standard Error And Deviation p Health Search databasePMCAll DatabasesAssemblyBioProjectBioSampleBioSystemsBooksClinVarCloneConserved DomainsdbGaPdbVarESTGeneGenomeGEO DataSetsGEO ProfilesGSSGTRHomoloGeneMedGenMeSHNCBI Web SiteNLM CatalogNucleotideOMIMPMCPopSetProbeProteinProtein ClustersPubChem BioAssayPubChem CompoundPubChem SubstancePubMedPubMed HealthSNPSparcleSRAStructureTaxonomyToolKitToolKitAllToolKitBookToolKitBookghUniGeneSearch termSearch Advanced Journal list convert standard error to standard deviation Help Journal ListClin Orthop Relat Resv SepPMC Clin Orthop p When To Use Standard Deviation Vs Standard Error p Relat Res Sep Published online May doi s - - - PMCID PMC In Brief calculate standard error from standard deviation in excel Standard Deviation and Standard ErrorDavid J Biau MD PhDDepartement de Biostatistique et Informatique Medicale H x f pital Saint-Louis avenue Claude Vellefaux Paris Cedex France p

relative standard error equation
Relative Standard Error Equation p estimates for Labour Force data News Media Media Centre ABS in the Media ABS Statistics Publications Release Dates Resources for Reporting Statistics Conferences Seminars and Events Contact Us Quick Links Consumer Price Index Unemployment p Relative Standard Error Excel p Rate Retail Trade Figures Building Approvals Figures GDP Trend Figures What is a Standard Error standard error formula and Relative Standard Error Reliability of estimates for Labour Force data On this page Why do we have Standard Errors Importance of Standard standard error vs standard deviation Errors Standard Error versus Relative Standard Error Example Further

relationship between confidence intervals and standard error
Relationship Between Confidence Intervals And Standard Error p DisclaimerPublic Health TextbookResearch Methods a - Epidemiology b - Statistical standard error and confidence limits worked example Methods c - Health Care Evaluation and Health Needs calculate confidence interval from standard error in r Assessment d - Qualitative MethodsDisease Causation and Diagnostic a - Epidemiological Paradigms b - Epidemiology of error intervals bitesize Diseases of Public Health Significance c - Diagnosis and Screening d - Genetics e - Health and Social Behaviour f - Environment g - Communicable Disease h p Error Intervals Maths p - Principles and Practice of Health Promotion

relative standard error proportion
Relative Standard Error Proportion p apply ABS Universities Australia agreement Published research About products and systems TableBuilder CURFs Census products Remote Access Data Laboratory RADL DataLab Log into your accounts TableBuilder - Population Census TableBuilder - Other data RADL Registration Centre MiCRO User guides and support relative standard error formula Census TableBuilder user guide tutorials TableBuilder user guide RADL user guide Responsible use of relative standard error excel microdata guide Microdata FAQs Terms and conditions Microdata contacts Sources of Variability There are two sources of uncertainty or variability associated with p Relative Standard Error Vs Relative Standard Deviation p survey