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# Standard Error Plus Minus Mean

a choice of exactly two possible values, one of which is the negation of the other. In experimental sciences, the sign commonly indicates the confidence interval or error in a measurement, often the standard deviation or standard

## Mean Plus Or Minus Standard Deviation Excel

error.[1] The sign may also represent an inclusive range of values that a reading plus or minus standard deviation or standard error might have. In engineering the sign indicates the tolerance, which is the range of values that are considered to be acceptable,

## Mean Plus Minus Standard Deviation Calculator

safe, or which comply with some standard, or with a contract.[2] In botany it is used in morphological descriptions to notate "more or less". In chemistry the sign is used to indicate a racemic mixture. how to calculate mean plus or minus standard deviation In chess, the sign indicates a clear advantage for the white player; the complementary sign ∓ indicates the same advantage for the black player.[3] The sign is normally pronounced "plus or minus". Contents 1 History 2 Usage 2.1 In mathematics 2.2 In statistics 2.3 In chess 3 Minus-plus sign 4 Encodings 4.1 Typing 5 Similar characters 6 See also 7 References History A version of the sign, including also the minus plus sign French word "ou" (meaning "or") was used in its mathematical meaning by Albert Girard in 1626, and the sign in its modern form was used as early as William Oughtred's Clavis Mathematicae (1631).[4] Usage In mathematics In mathematical formulas, the ± symbol may be used to indicate a symbol that may be replaced by either the + or − symbols, allowing the formula to represent two values or two equations. For example, given the equation x2 = 1, one may give the solution as x = ±1. This indicates that the equation has two solutions, each of which may be obtained by replacing this equation by one of the two equations x = +1 or x = −1. Only one of these two replaced equations is true for any valid solution. A common use of this notation is found in the quadratic formula x = − b ± b 2 − 4 a c 2 a . {\displaystyle \displaystyle x={\frac {-b\pm {\sqrt {b^{2}-4ac}}}{2a}}.} describing the two solutions to the quadratic equation ax2+bx+c=0. Similarly, the trigonometric identity sin ⁡ ( A ± B ) = sin ⁡ ( A ) cos ⁡ ( B ) ± cos ⁡ ( A ) sin ⁡ ( B ) . {\displaystyle \sin(A\pm B

a choice of exactly two possible values, one of which is the negation of the other. In experimental sciences, the sign commonly indicates the confidence

## Plus Minus Symbol Word

interval or error in a measurement, often the standard deviation or standard plus minus symbol keyboard shortcut error.[1] The sign may also represent an inclusive range of values that a reading might have. In

## Mean Plus Or Minus 2 Standard Deviations

engineering the sign indicates the tolerance, which is the range of values that are considered to be acceptable, safe, or which comply with some standard, or with a contract.[2] https://en.wikipedia.org/wiki/Plus-minus_sign In botany it is used in morphological descriptions to notate "more or less". In chemistry the sign is used to indicate a racemic mixture. In chess, the sign indicates a clear advantage for the white player; the complementary sign ∓ indicates the same advantage for the black player.[3] The sign is normally pronounced "plus or minus". Contents 1 https://en.wikipedia.org/wiki/Plus-minus_sign History 2 Usage 2.1 In mathematics 2.2 In statistics 2.3 In chess 3 Minus-plus sign 4 Encodings 4.1 Typing 5 Similar characters 6 See also 7 References History A version of the sign, including also the French word "ou" (meaning "or") was used in its mathematical meaning by Albert Girard in 1626, and the sign in its modern form was used as early as William Oughtred's Clavis Mathematicae (1631).[4] Usage In mathematics In mathematical formulas, the ± symbol may be used to indicate a symbol that may be replaced by either the + or − symbols, allowing the formula to represent two values or two equations. For example, given the equation x2 = 1, one may give the solution as x = ±1. This indicates that the equation has two solutions, each of which may be obtained by replacing this equation by one of the two equations x = +1 or x = −1. Only one of these two replaced equations is true for any valid solution. A common use of this nota

does this plus-minus statistics sign mean in layman's terms?Does this mean that patients with PHPT had their calcium go up and down between point 33 and point 44 ? What does that "0.4 +- 0.33 mg/dl" thing mean ?UpdateCancelAnswer https://www.quora.com/What-does-this-plus-minus-statistics-sign-mean-in-laymans-terms Wiki5 Answers Erik Madsen, A dismal scientistWritten 200w ago · Upvoted by Justin Rising, PhD in statisticsAt a very basic level, the notation "x ± y" in a scientific paper is simply a shorthand for reporting that the mean of a sample is x while its standard error (that is, its standard deviation divided by sqrt(sample size)) is y. [1]However, like many notational conventions, this one is meant to be suggestive. standard deviation The "±" symbol is used to signal that the population quantity we are attempting to estimate from our sample is in some sense likely to lie in the interval [x - y, x + y]. I'll try to lay out the precise sense in which this is true. (I assert that a determined layperson should be able to follow most of the discussion below. If not, just skip to the tl;dr plus or minus at the end.)Any standard frequentist textbook will state the following Central Limit Theorem: Given the opportunity to repeatedly and independently sample from a population with mean mu and standard deviation sigma, the mean of a sample of size N from that distribution will be approximately normally distributed with mean mu and standard deviation sigma/sqrt(N), provided N is sufficiently large. From this fact you can compute coverage intervals of the form $\left[\mu - z_\alpha \frac{\sigma}{\sqrt{N}}, \mu + z_\alpha \frac{\sigma}{\sqrt{N}}\right]$which have the property that any particular sample mean of size N will lie in the coverage interval with probability approximately 1 - alpha (with the approximation becoming exact when N grows large). The scale factors z_alpha get bigger as alpha grows smaller (you need larger intervals to cover the outcome with higher probability), and they can be computed from tables of standard normal quantiles. For instance, z_{0.317} = 1 and z_{0.05} = 1.96.This result suggests that if you replace the true population mean mu with the sample mean x, you can construct an interval that gives you values of the underlying distribution mean that are "likely" to have generated your sample. This technique works and is called "inverting the test statistic". The resulting confidence interval [math]\left[x - z_\alpha \frac{\sigma}{\sqrt{N}}, x + z_\alpha \frac{\sigma}{\sqrt{N}}\righ

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