Expectation of Difference of Random Variables Solution

STEP 0: Pre-Calculation Summary
Formula Used
Expectation of Difference of Random Variables = Expectation of Random Variable X-Expectation of Random Variable Y
E(X-Y) = E(X)-E(Y)
This formula uses 3 Variables
Variables Used
Expectation of Difference of Random Variables - Expectation of Difference of Random Variables is the average value or mean of the differences between two random variables.
Expectation of Random Variable X - Expectation of Random Variable X is the average value or mean of the random variable X.
Expectation of Random Variable Y - Expectation of Random Variable Y is the average value or mean of the random variable Y.
STEP 1: Convert Input(s) to Base Unit
Expectation of Random Variable X: 36 --> No Conversion Required
Expectation of Random Variable Y: 34 --> No Conversion Required
STEP 2: Evaluate Formula
Substituting Input Values in Formula
E(X-Y) = E(X)-E(Y) --> 36-34
Evaluating ... ...
E(X-Y) = 2
STEP 3: Convert Result to Output's Unit
2 --> No Conversion Required
FINAL ANSWER
2 <-- Expectation of Difference of Random Variables
(Calculation completed in 00.004 seconds)

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Shri Madhwa Vadiraja Institute of Technology and Management (SMVITM), Udupi
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18 Basic Formulas in Statistics Calculators

P Value of Sample
Go P Value of Sample = (Sample Proportion-Assumed Population Proportion)/sqrt((Assumed Population Proportion*(1-Assumed Population Proportion))/Sample Size)
Sample Size given P Value
Go Sample Size = ((P Value of Sample^2)*Assumed Population Proportion*(1-Assumed Population Proportion))/((Sample Proportion-Assumed Population Proportion)^2)
t Statistic of Normal Distribution
Go t Statistic of Normal Distribution = (Sample Mean-Population Mean)/(Sample Standard Deviation/sqrt(Sample Size))
t Statistic
Go t Statistic = (Observed Mean of Sample-Theoretical Mean of Sample)/(Sample Standard Deviation/sqrt(Sample Size))
Chi Square Statistic
Go Chi Square Statistic = ((Sample Size-1)*Sample Standard Deviation^2)/(Population Standard Deviation^2)
Number of Classes given Class Width
Go Number of Classes = (Largest Item in Data-Smallest Item in Data)/Class Width of Data
Class Width of Data
Go Class Width of Data = (Largest Item in Data-Smallest Item in Data)/Number of Classes
Expectation of Difference of Random Variables
Go Expectation of Difference of Random Variables = Expectation of Random Variable X-Expectation of Random Variable Y
Chi Square Statistic given Sample and Population Variances
Go Chi Square Statistic = ((Sample Size-1)*Sample Variance)/Population Variance
Expectation of Sum of Random Variables
Go Expectation of Sum of Random Variables = Expectation of Random Variable X+Expectation of Random Variable Y
Number of Individual Values given Residual Standard Error
Go Number of Individual Values = (Residual Sum of Squares/(Residual Standard Error of Data^2))+1
F Value of Two Samples given Sample Standard Deviations
Go F Value of Two Samples = (Standard Deviation of Sample X/Standard Deviation of Sample Y)^2
Mid Range of Data
Go Mid Range of Data = (Maximum Value of Data+Minimum Value of Data)/2
F Value of Two Samples
Go F Value of Two Samples = Variance of Sample X/Variance of Sample Y
Smallest Item in Data given Range
Go Smallest Item in Data = Largest Item in Data-Range of Data
Largest Item in Data given Range
Go Largest Item in Data = Range of Data+Smallest Item in Data
Range of Data
Go Range of Data = Largest Item in Data-Smallest Item in Data
Relative Frequency
Go Relative Frequency = Absolute Frequency/Total Frequency

Expectation of Difference of Random Variables Formula

Expectation of Difference of Random Variables = Expectation of Random Variable X-Expectation of Random Variable Y
E(X-Y) = E(X)-E(Y)

What is Expectation of random variables in Statistics?

In probability theory, the expected value (also called expectation, expectancy, mathematical expectation, mean, average, or first moment) is a generalization of the weighted average. Informally, the expected value is the arithmetic mean of a large number of independently selected outcomes of a random variable.
The expected value of a random variable with a finite number of outcomes is a weighted average of all possible outcomes. In the case of a continuum of possible outcomes, the expectation is defined by integration. In the axiomatic foundation for probability provided by measure theory, the expectation is given by Lebesgue integration.

How to Calculate Expectation of Difference of Random Variables?

Expectation of Difference of Random Variables calculator uses Expectation of Difference of Random Variables = Expectation of Random Variable X-Expectation of Random Variable Y to calculate the Expectation of Difference of Random Variables, Expectation of Difference of Random Variables formula is defined as the average value or mean of the differences between two random variables. Expectation of Difference of Random Variables is denoted by E(X-Y) symbol.

How to calculate Expectation of Difference of Random Variables using this online calculator? To use this online calculator for Expectation of Difference of Random Variables, enter Expectation of Random Variable X (E(X)) & Expectation of Random Variable Y (E(Y)) and hit the calculate button. Here is how the Expectation of Difference of Random Variables calculation can be explained with given input values -> 25 = 36-34.

FAQ

What is Expectation of Difference of Random Variables?
Expectation of Difference of Random Variables formula is defined as the average value or mean of the differences between two random variables and is represented as E(X-Y) = E(X)-E(Y) or Expectation of Difference of Random Variables = Expectation of Random Variable X-Expectation of Random Variable Y. Expectation of Random Variable X is the average value or mean of the random variable X & Expectation of Random Variable Y is the average value or mean of the random variable Y.
How to calculate Expectation of Difference of Random Variables?
Expectation of Difference of Random Variables formula is defined as the average value or mean of the differences between two random variables is calculated using Expectation of Difference of Random Variables = Expectation of Random Variable X-Expectation of Random Variable Y. To calculate Expectation of Difference of Random Variables, you need Expectation of Random Variable X (E(X)) & Expectation of Random Variable Y (E(Y)). With our tool, you need to enter the respective value for Expectation of Random Variable X & Expectation of Random Variable Y and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.
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