Average Standard Error
Contents |
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 about Stack Overflow the company Business Learn more about hiring developers mean standard error or posting ads with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross median standard error Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it percentage standard error only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top Calculate average of a set numbers with reported standard errors up
Average Standard Deviation
vote 4 down vote favorite 3 I have 365 daily measurements that all have standard errors associated with them. Date | Prediction | Standard Error ----------------------------------------- Jan-01-2003 | 24.8574 | 10.6407 Jan-02-2003 | 10.8658 | 3.8237 Jan-03-2003 | 12.1917 | 5.7988 Jan-04-2003 | 11.1783 | 4.3016 Jan-05-2003 | 16.713 | 5.3177 etc ... What is the statistically appropriate way of getting the yearly average with a 95% Confidence Interval around it ? I am assuming that the errors must be propagating average percent error somehow and need to be accounted for. Google returns mostly information on how to calculate the average or standard deviation of a set of numbers, not a set of numbers with errors. I would also appreciate some type of internet reference so I can refer to it later. references average error-propagation share|improve this question edited Sep 12 '13 at 10:05 Comp_Warrior 1,272926 asked Jan 13 '12 at 21:00 user918967 16819 migrated from stackoverflow.com Jan 15 '12 at 5:03 This question came from our site for professional and enthusiast programmers. Do you know if the data normally distributed? –ahoffer Jan 13 '12 at 22:06 I do not. For sake of argument we can say it is but it is likely Poisson because much of the other data I work with usually is. –user918967 Jan 14 '12 at 5:15 The Poisson distribution is used for discrete data whereas your data seems to be continuous. What I would like to know is how the standard errors were obtained. Are they related to the measrements themselves or were they somehow obtained separately? –MansT Jan 15 '12 at 9:11 An average is just a the sum of each item times its proportion. In the case of a normal average these would just be equal for each item (summing to 1 of course). So Is it appropriate to just use normal addition error propagation after multiplying by the prop
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 about Stack Overflow the company Business Learn average confidence interval more about hiring developers or posting ads with us Cross Validated Questions Tags Users Badges
Average Variance
Unanswered Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining,
Average Coefficient Of Variation
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 The best answers are voted up and rise to the top How to 'sum' a http://stats.stackexchange.com/questions/21104/calculate-average-of-a-set-numbers-with-reported-standard-errors standard deviation? up vote 30 down vote favorite 17 I have a monthly average for a value and a standard deviation corresponding to that average. I am now computing the annual average as the sum of monthly averages, how can I represent the standard deviation for the summed average ? For example considering output from a wind farm: Month MWh StdDev January 927 333 February 1234 250 March 1032 301 April 876 204 May 865 165 June http://stats.stackexchange.com/questions/25848/how-to-sum-a-standard-deviation 750 263 July 780 280 August 690 98 September 730 76 October 821 240 November 803 178 December 850 250 We can say that in the average year the wind farm produces 10,358 MWh, but what is the standard deviation corresponding to this figure ? standard-deviation summary-statistics share|improve this question edited Apr 5 '12 at 6:34 asked Apr 4 '12 at 15:22 klonq 310248 3 A discussion following a now-deleted reply noted a possible ambiguity in this question: do you seek the SD of the monthly averages or do you want to recover the SD of all the original values from which those averages were constructed? That reply also correctly pointed out that if you want the latter, you will need the numbers of values involved in each one of the monthly averages. –whuber♦ Apr 4 '12 at 17:37 1 A comment to another deleted reply pointed out that it is strange to compute an average as a sum: surely you mean that you are averaging the monthly averages. But if what you want is to estimate the average of all the original data, then such a procedure is not usually a good one: a weighted average is needed. And of course it's not possible to give a good answer to your question about the "SD for the summed average" until it is clear what the "su
Academic Journals Tips For KidsFor Kids How to Conduct Experiments Experiments With Food Science Experiments Historic Experiments Self-HelpSelf-Help Self-Esteem Worry Social Anxiety Arachnophobia Anxiety SiteSite About FAQ Terms Privacy https://explorable.com/standard-error-of-the-mean Policy Contact Sitemap Search Code LoginLogin Sign Up Standard Error of http://docs.scipy.org/doc/numpy/reference/generated/numpy.std.html the Mean . Home > Research > Statistics > Standard Error of the Mean . . . Siddharth Kalla 283.8K reads Comments Share this page on your website: Standard Error of the Mean The standard error of the mean, also called the standard standard error deviation of the mean, is a method used to estimate the standard deviation of a sampling distribution. To understand this, first we need to understand why a sampling distribution is required. This article is a part of the guide: Select from one of the other courses available: Scientific Method Research Design Research Basics Experimental Research Sampling average standard error Validity and Reliability Write a Paper Biological Psychology Child Development Stress & Coping Motivation and Emotion Memory & Learning Personality Social Psychology Experiments Science Projects for Kids Survey Guide Philosophy of Science Reasoning Ethics in Research Ancient History Renaissance & Enlightenment Medical History Physics Experiments Biology Experiments Zoology Statistics Beginners Guide Statistical Conclusion Statistical Tests Distribution in Statistics Discover 17 more articles on this topic Don't miss these related articles: 1Calculate Standard Deviation 2Variance 3Standard Deviation 4Normal Distribution 5Assumptions Browse Full Outline 1Frequency Distribution 2Normal Distribution 2.1Assumptions 3F-Distribution 4Central Tendency 4.1Mean 4.1.1Arithmetic Mean 4.1.2Geometric Mean 4.1.3Calculate Median 4.2Statistical Mode 4.3Range (Statistics) 5Variance 5.1Standard Deviation 5.1.1Calculate Standard Deviation 5.2Standard Error of the Mean 6Quartile 7Trimean 1 Frequency Distribution 2 Normal Distribution 2.1 Assumptions 3 F-Distribution 4 Central Tendency 4.1 Mean 4.1.1 Arithmetic Mean 4.1.2 Geometric Mean 4.1.3 Calculate Median 4.2 Statistical Mode 4.3 Range (Statistics) 5 Variance 5.1 Standard Deviation 5.1.1 Calculate Standard Deviation 5.2 Standard Error of the Mean 6 Quartile 7 Trimean . As a
Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis. Parameters:a : array_like Calculate the standard deviation of these values. axis : None or int or tuple of ints, optional Axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array. If this is a tuple of ints, a standard deviation is performed over multiple axes, instead of a single axis or all the axes as before. dtype : dtype, optional Type to use in computing the standard deviation. For arrays of integer type the default is float64, for arrays of float types it is the same as the array type. out : ndarray, optional Alternative output array in which to place the result. It must have the same shape as the expected output but the type (of the calculated values) will be cast if necessary. ddof : int, optional Means Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. By default ddof is zero. keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original arr. Returns:standard_deviation : ndarray, see dtype parameter above. If out is None, return a new array containing the standard deviation, otherwise return a reference to the output array. See also var, mean, nanmean, nanstd, nanvar numpy.doc.ufuncs Section "Output arguments" Notes The standard deviation is the square root of the average of the squared deviations from the mean, i.e., std = sqrt(mean(abs(x - x.mean())**2)). The average squared deviation is normally c