Refers to the standard deviation of the sampling distribution of a statistic calculated from a sample. Standard errors are often required when forming confidence intervals or testing hypotheses about the population from which the statistic was sampled.

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Interpreting the value of standard errors [duplicate]

After computing the standard error of regression, my answer is 3.55 what does the value mean
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21 views

Selecting priors based on measurement error

How do you calculate the appropriate prior if you have the measurement error of an instrument? This paragraph is from Cressie's book "Statistics for Spatio-Temporal Data": It is often the case ...
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1answer
19 views

Does the calculation of error bars in lme4 require the Cosineau (2005) correction?

In Cosineau (2005) a method for calculating within-subject design error bars which removes the between subjects variance before calculating confidence intervals, error bars and so on is suggested. I ...
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20 views

Asymmetric Error Bars [on hold]

My question is about the application scenario of asymmetric error bars and how to calculate different positive and negative error limits in error bars. I know in symmetric error bars, we can calculate ...
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5 views

More appropriate relative standard error interpretation/calculation

To estimate the proportional change from a reference value for a given covariate, I am trying to understand which method is more appropriate from an interpretation of the precision of the estimate. ...
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46 views

OLS standard error that corrects for autocorrelation but not heteroskedasticity

Question: By mapping the OLS regression into the GMM framework, write the formula for the standard error of the OLS regression coefficients that corrects for autocorrelation but not ...
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195 views

Why don't we use the unbiased sample variance to calculate the standard error?

The standard error is an approximation of the standard deviation of the sampling distribution of the sample means. The real standard deviation of the sampling distribution, $\sigma _{\bar x}$ is: ...
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12 views

logarithmic calibration and geometric mean - citation search

I have a logarithmic calibration line: MachineSignal = -3.21 log(concentration) + 21.9 It seems obvious to me, that if I have a triplicate measurement of concentrations (measured indirectly through ...
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7 views

How to calculate MoE for subsamples

I have demographic and income data for 3 million people from the American Community Survey (courtesy of IPUMS), and my goal is calculate the median income for every permutation of age group, gender, ...
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2answers
155 views

Why do we have to assume normality for a one-sample t-test?

As a consequence of the central limit theorem the sampling distribution of the sample means will always be normal whatever is the distribution of the variable we measure. From our sample we can ...
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53 views

Standard error of proportions, with weighting

I have a set of experiments $i=1\dots k$ each of which performs $n_i$ binomial experiments, recording a fraction $p_i$ successes. Clearly if I trust all of the experiments equally, my estimated ...
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10 views

histograms/ kernel density estimation for proportion data

I am looking at digital advertising data with the following columns: site_id | impressions_count| clicks_count. I am interested in a histogram of the click through rate (clicks/impressions) across ...
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1answer
38 views

Standard error bars overlap but significance - estimated marginal means versus observed means

I'm running a Mixed effects model ANOVA with two fixed factors (condition, repetition) and one random factor (subject). Subsequently, a Tukey multiple comparisons test is performed. Now I'd like to ...
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1answer
105 views

Why autocorrelation affects OLS coefficient standard errors?

It seems that OLS residuals autocorrelation is not always an issue, depending on the problem at hand. But why residuals autocorrelation would affect the coefficient standard errors? From the Wikipedia ...
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2answers
68 views

How can I calculate t-score without knowing true population mean?

I am studying now t-scores. As far as I understand, t-scores are used when we don't know true population parameters (such as: standard deviation and population mean) and cant use z-scores. Here is ...
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50 views

Calculating the Net Promoter Score for poll data on a 1-5 scale

From Wikipedia The Net Promoter Score is obtained by asking customers a single question on a 0 to 10 rating scale, where 10 is "extremely likely" and 0 is "not at all likely": "How likely is ...
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2answers
78 views

How to compute (or numerically estimate) the standard error of the MLE

I have a model for which I know the log likelihood function, the gradient of the log likelihood and the Hessian of the log likelihood. For given data I can compute the MLE using a generic optimizer ...
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1answer
25 views

Assuming the true mean

I've collected fluorescence data from some bacterial cells. Each cell has a gene in it which can be induced to fluoresce. However, even without being induced, the gene will still fluoresce a little. ...
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1answer
29 views

Adjust standard errors for within correlation

I am trying to replicate a table and in one of the notes it's written that 'standard errors are adjusted to account for the within-analyst correlation of the observations' I am running my regressions ...
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3answers
62 views

Analytic or sample standard deviation with binomial data

I've been looking for recommendations on whether it's better to use the sample standard deviation (SD) for a binomial distribution or use the analytic SD (or variance). It's for experiments with ...
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9 views

Standard error for expected value [duplicate]

I have a computer simulation from which I get a sample of values of some microscopic quantity $X$, i.e. $\{ x_1,\ldots,x_N \}$. I'm interested in estimating the expected value of $X$, i.e. $E[ ...
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20 views

Mean squared error / Max error squared

I'm use this metric for variation that is similar to CV, but it is guaranteed to be on a 0 to 2 scale for positive numbers, where 2 is "all over the place" and 0 is "perfectly even". Since its ...
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error on truncated rms

I am computing the RMS of a sample to estimate the standar error $\sigma$ of the underlying distribution (for simplicity let say a normal distribution $N[\mu$, $\sigma$]). $ \text{RMS} = \sum_{i=1}^N ...
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Proper back-transformation of lognormal standard deviation to find confidence intervals around a mean [duplicate]

I want to determine the 95% confidence interval of a mean. I logged-transformed my data in order to achieve a normal distribution. Several observations contained 0, so I changed these to 1 so that ...
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Standard error of mean for a distribution with two dependent variables

I want to calculate the mean and standard error of the mean for the amount spent per person visiting a store. Most people don't buy anything, so the distribution looks like this ${\rm P}({\rm ...
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How does Standard Deviation (Error) change with sample size change in this scenario. Explanation needed for a nonprofessional

I have this question that I want figured out. A person's Blood pressure was taken 4 times,the mean of these 4 observations came out to be say 120mm of Hg And the SD was 2.5. Now we have taken 4 more ...
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Obtaining Standard Error of Weighted Averages using Bootstrapping?

My problem is finding a way to estimate the standard error of a flow-weighted mean concentration. The FWMC is computed by summing the years flow * concentration measurements and dividing by the sum of ...
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33 views

$R^2$ equal square of sample correlation [duplicate]

I?m having a hard time proving that $R^2$ is equal to the square of the sample correlation between $Y$ and $\hat{Y}$. Every book I search tells me that's very easy, like verbeek. They just state that ...
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Piecewise linear / spline regression: explaining changes in standard error

I have a model to estimate the effect of gas prices on a dependent variable Y. In the piecewise linear regression model (Gujarati 1995, p.519), I included a dummy ...
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44 views

Sum of Variance or Standard Error?

My end goal is to present the average travel time for a corridor and the standard deviation (or standard error) of that travel time. I'm not sure what to present to be statistically correct, here is ...
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50 views

Interpreting coefficient errors in regression from uncertain population

I'm working on some regressions for UK cities and have a question about how to interpret regression coefficients. In a typical regression, one would be working with data from a sample and so the ...
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1answer
82 views

Should you report variance of asymmetrical data, such as ratios?

I have measured the time taken to solve a problem by algorithm $X$ and by algorithm $Y$. It takes a quite long time, so I have only 10 data for each algorithm: $$ X : ( x_1, x_2, \dots , x_{10}) \\ Y ...
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1answer
83 views

Error on interquartile range

How can I compute the error on the interquartile range of a sample? By error I mean its std deviation (e.g. error on the mean = RMS/sqrt(N)). The sample is from a unimodal distribution, similar to ...
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69 views

How to calculate standard error of sample quantile from normal distribution with known mean and standard deviation?

I know that the standard error of the mean for an iid sample is calculated as $$\frac{\sigma}{\sqrt{n}}$$ However, assuming a normal distribution with known mean and standard deviation, how do you ...
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Do you need to report the standard error of the mean when the sample is the population?

The other day, my tutor told me that whenever a mean value is reported, the standard error of the mean must be reported alongside. But surely this isn't always the case? For example, let's say we ...
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2answers
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Standard error of the sampling distribution of the mean

I found an equation that says the standard error of the sampling distribution of the mean is: $$\sigma_{\bar{X}} = \sigma \cdot \sqrt{\frac{1}{n}-\frac{1}{N}}$$ And when the population size is very ...
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39 views

How would I factor study design into relative risk?

I'm comparing various conditions versus some disease for a large stratified/clustered dataset which purports to account for the entire population after weighting -- hence the use of RR instead of OR. ...
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1answer
33 views

Does the standard error assume the mean is the centre of the distribution?

In statistics we can calculate a mean of a sample and the standard error of the mean. Let's say the mean of a sample is 2 and the standard error 1.5. If we repeatedly sampled from this population, it ...
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16 views

How do I account for within-subject variance to produce the standard error of the mean for different between-subject groups?

I have a mixed design with 25 subjects each with 4 repeated measurements in each of three different between subject treatment groups (total n=75). I want to produce the standard error of the mean for ...
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32 views

Which statistics to use calculating prediction interval of dummy linear regression?

I have performed a linear regression and found a model of the form: $$ \hat{Y} = \alpha + \beta_1 x+ \delta_{high} + \delta_{low} + \epsilon\\ $$ Where: $\beta_1$ is a continuously distributed ...
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24 views

How to calculate the standard deviation from a normalised value?

I have 2 data sets (I have more but for simplicity lets say I have 2). Data 1 0.15239652 0.145848036 0.175981261 Data 2 0.417902092 0.342696648 0.354871141 I ...
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39 views

How to compute Newey West standard errors and t-statistics

I'm currently trying to use Newey-West standard errors accounting for Heteroskedasticity and Autocorrelation with the sandwich package in R, but i lack understanding as i can not fully grasp the ...
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1answer
169 views

Calculating effect sizes and standard errors for the difference between two standardized mean differences

I have two related questions, both of which are related to a meta-analysis I am performing where where the primary outcomes are expressed in terms of the standardized mean difference. My studies have ...
2
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0answers
52 views

Standard error on median for exponential distribution

I am trying to find the standard error on the median, $\sigma_\tilde{x}$, for a sample, $X_i$, of a population whose pdf could be modelled as $\lambda e^{-\lambda x} $ if normalized. To make sure we ...
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14 views

How to select an error/weight for two-dimensional binned data?

Beginning with noisy data vectors $\mathbf{x}$ and $\mathbf{y}$, I have binned the data to vectors $\mathbf{x}_b$ and $\mathbf{y}_b$ of length $N_b$ with fixed linear ($\mathbf{x}_b^i - ...
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28 views

Standard Errors of Transformed Variables

I am carrying out an MLE where some I use a log transformation on the variance parameters which are being optimized. When I calculate the standard errors (se) the se of the transformed variables is ...
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1answer
33 views

Standard error of difference of estimates

I have two (non-independent) OLS-parameter estimates each with its own standard error. I'm trying to find out what the standard error of the difference of the estimates should be. Can anyone help? Is ...
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Relative importance of variables?

The following output is given: The task is to state, which variables, among thoses that are statistically significnat at 0.05, have the greatest and least relative importance on the fitted model? ...
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33 views

Standard Error of a linear regression

As defined here, the estimation of the coefficient of correlation is $$r = \frac{\Sigma (X_i-E[X])(Y_i-E[Y])}{\sqrt { \Sigma (X_i-E[X])^2 \Sigma (Y_i - E[Y])^2}}$$ and the standard error of $r$ is ...
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139 views

Any alternative way to compute standard errors for maximum likelihood estimates?

I am dealing with an example stated in here. Given the same data in the above link and following a parametric bootstrap method suggested in here, I computed the standard errors for maximum ...