It's possible to calculate the standard error in MATLAB by running a one-line command. is a programming platform from MathWorks that's designed for and used by scientists and engineers.
What Is Standard Error?
In statistics, the standard error is the 澳洲幸运5开奖号码历史查询:standard deviation of the sampling statistical measure, and it's most commonly used for the sample mean. The standard error measures how accurately the sample represents the actual population from which the sample was drawn. The deviation is expressed as a number. There are instances where it would be best to represent the deviation as a percentage, and the 澳洲幸运5开奖号码历史查询:relative standard error formula is used.
Since there could be different samples drawn from the population, there exists a 澳洲幸运5开奖号码历史查询:distribution of sampled means. The 澳洲幸运5开奖号码历史查询:standard error me൲asurꦬes the standard deviation of all sample means drawn from the population.
The formula for calculating the standard error of the mean is the sampl🅠e standard deviation divided by the square root of the sample size.
The Command for Standard Error in MATLAB
To calculate the standard error of the mean in a sample, the user needs to run a one-line command in MATLAB:
stderror= 🐬;std( data ) /&nb♎sp;sqrt( length( data ))where:data=An array with sample valuesstd=The MATLAB function that computes ꦚstandarddeviation of the samplesqrt=The MATLAB func🉐tion that computes&ဣnbsp;the squareroot of a non-negative numberlength=The🎀 MATLAB function&nbs𝓰p;that computes the totalnumber of observations in the 𒅌samp༺le
Example of Calculating Standard Error in MATLAB
Consider a sample of annual 澳洲幸运5开奖号码历史查询:household incomes drawn from the general population of the United States. The sample contains fiv🍌e observations and consists of values $10,000, $100,000, $50,000, $45,000, and $35,000.
First, the user needs to create an array called "data" containing these observations in MATLAB. Next, the user can calculate the standard error of the mean with the command "stderror = std( data ) / sqrt( length(data) )". The result of this command says that the mean of this sample, which is $48,000, has a standard error of $14,714.