Most Probable Value with Same Weightage for Observations Calculator

✖Sum of Observed Values is the total added value of individual observed values or measured values.ⓘ Sum of Observed Values [Ʃx_i]			+10% -10%
✖Number of Observations refers to the number of observations taken in the given data collection.ⓘ Number of Observations [n_obs]			+10% -10%

✖Most probable value of a quantity is the one which has more chances of being true than has any other. It is deduced from the several measurements on which it is based.ⓘ Most Probable Value with Same Weightage for Observations [MPV]

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Most Probable Value with Same Weightage for Observations

Formula

`"MPV" = "Ʃx"_{"i"}/"n"_{"obs"}`

Example

`"200"="800"/"4"`

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Most Probable Value with Same Weightage for Observations Solution

STEP 0: Pre-Calculation Summary

Formula Used

Most Probable Value = Sum of Observed Values/Number of Observations
MPV = Ʃx_i/n_obs
This formula uses 3 Variables

Variables Used

Most Probable Value - Most probable value of a quantity is the one which has more chances of being true than has any other. It is deduced from the several measurements on which it is based.
Sum of Observed Values - Sum of Observed Values is the total added value of individual observed values or measured values.
Number of Observations - Number of Observations refers to the number of observations taken in the given data collection.

STEP 1: Convert Input(s) to Base Unit

Sum of Observed Values: 800 --> No Conversion Required
Number of Observations: 4 --> No Conversion Required

STEP 2: Evaluate Formula

Substituting Input Values in Formula

MPV = Ʃx_i/n_obs --> 800/4

Evaluating ... ...

MPV = 200

STEP 3: Convert Result to Output's Unit

200 --> No Conversion Required

FINAL ANSWER

200 <-- Most Probable Value

(Calculation completed in 00.004 seconds)

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Created by Chandana P Dev

NSS College of Engineering (NSSCE), Palakkad

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Meerut Institute of Engineering and Technology (MIET), Meerut

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< 21 Theory of Errors Calculators

Standard Error of Function where variables are Subjected to Addition

Go Standard Error in Function = sqrt(Standard Error in x coordinate^2+Standard Error in y coordinate^2+Standard Error in z coordinate^2)

Most Probable Value with Different Weightage

Go Most Probable Value = add(Weightage*Measured Quantity)/add(Weightage)

Standard Deviation of Weighted Observations

Go Weighted Standard Deviation = sqrt(Sum of Weighted Residual Variation/(Number of Observations-1))

Standard Deviation used for Survey Errors

Go Standard Deviation = sqrt(Sum of Square of Residual Variation/(Number of Observations-1))

Mean Error given Specified Error of Single Measurement

Go Error of Mean = Specified Error of a Single Measurement/(sqrt(Number of Observations))

Standard Error of Mean of Weighted Observations

Go Standard Error of Mean = Weighted Standard Deviation/sqrt(Sum of Weightage)

Probable Error of Mean

Go Probable Mean of Error = Probable Error in Single Measurement/(Number of Observations^0.5)

Variance of Observations

Go Variance = Sum of Square of Residual Variation/(Number of Observations-1)

Mean Error given Sum of Errors

Go Error of Mean = Sum of Errors of Observations/Number of Observations

Most Probable Value with Same Weightage for Observations

Go Most Probable Value = Sum of Observed Values/Number of Observations

Residual Variation given Most Probable Value

Go Residual Variation = Measured Value-Most Probable Value

Most Probable Value given Residual Error

Go Most Probable Value = Observed Value-Residual Error

Observed Value given Residual Error

Go Observed Value = Residual Error+Most Probable Value

Residual Error

Go Residual Error = Observed Value-Most Probable Value

Observed Value given Relative Error

Go Observed Value = True Error/Relative Error

True Error given Relative Error

Go True Error = Relative Error*Observed Value

Relative Error

Go Relative Error = True Error/Observed Value

Observed Value given True Error

Go Observed Value = True Value-True Error

True Value given True Error

Go True Value = True Error+Observed Value

True Error

Go True Error = True Value-Observed Value

Most Probable Error given Standard Deviation

Go Most Probable Error = 0.6745*Standard Deviation

Most Probable Value with Same Weightage for Observations Formula

Most Probable Value = Sum of Observed Values/Number of Observations
MPV = Ʃx_i/n_obs

What is Geodetic Surveying?

The object of the geodetic surveying is to determine very precisely the relative or absolute positions on the earth’s surface of a system of widely separated points. The relative positions are determined in terms of the lengths and azimuths of the lines joining them

How to Calculate Most Probable Value with Same Weightage for Observations?

Most Probable Value with Same Weightage for Observations calculator uses Most Probable Value = Sum of Observed Values/Number of Observations to calculate the Most Probable Value, The Most Probable Value with Same Weightage for Observations formula is defined as the value, which is closer to the true value, but the weightage of measured values is all the same. Most Probable Value is denoted by MPV symbol.

How to calculate Most Probable Value with Same Weightage for Observations using this online calculator? To use this online calculator for Most Probable Value with Same Weightage for Observations, enter Sum of Observed Values (Ʃx_i) & Number of Observations (n_obs) and hit the calculate button. Here is how the Most Probable Value with Same Weightage for Observations calculation can be explained with given input values -> 200 = 800/4.

FAQ

What is Most Probable Value with Same Weightage for Observations?

The Most Probable Value with Same Weightage for Observations formula is defined as the value, which is closer to the true value, but the weightage of measured values is all the same and is represented as MPV = Ʃx_i/n_obs or Most Probable Value = Sum of Observed Values/Number of Observations. Sum of Observed Values is the total added value of individual observed values or measured values & Number of Observations refers to the number of observations taken in the given data collection.

How to calculate Most Probable Value with Same Weightage for Observations?

The Most Probable Value with Same Weightage for Observations formula is defined as the value, which is closer to the true value, but the weightage of measured values is all the same is calculated using Most Probable Value = Sum of Observed Values/Number of Observations. To calculate Most Probable Value with Same Weightage for Observations, you need Sum of Observed Values (Ʃx_i) & Number of Observations (n_obs). With our tool, you need to enter the respective value for Sum of Observed Values & Number of Observations and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.

How many ways are there to calculate Most Probable Value?

In this formula, Most Probable Value uses Sum of Observed Values & Number of Observations. We can use 2 other way(s) to calculate the same, which is/are as follows -

Most Probable Value = add(Weightage*Measured Quantity)/add(Weightage)
Most Probable Value = Observed Value-Residual Error

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