Regression Constant Calculator

✖Mean of Y is the average value of all the data points in the variable Y.ⓘ Mean of Y [ȳ]			+10% -10%
✖Regression Coefficient is the value that represents the change in the dependent variable Y for a unit change in the independent variable X.ⓘ Regression Coefficient [b₁]			+10% -10%
✖Mean of X is the average value of all the data points in the variable X.ⓘ Mean of X [x̅]			+10% -10%

✖Regression Constant is the intercept of the regression line on the Y-axis. It represents the expected value of Y when X is 0.ⓘ Regression Constant [b₀]

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Formula

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Regression Constant

Formula

`"b"_{"0"} = "ȳ"-("b"_{"1"}*"x̅")`

Example

`"50"="200"-("5"*"30")`

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Regression Constant Solution

STEP 0: Pre-Calculation Summary

Formula Used

Regression Constant = Mean of Y-(Regression Coefficient*Mean of X)
b₀ = ȳ-(b₁*x̅)
This formula uses 4 Variables

Variables Used

Regression Constant - Regression Constant is the intercept of the regression line on the Y-axis. It represents the expected value of Y when X is 0.
Mean of Y - Mean of Y is the average value of all the data points in the variable Y.
Regression Coefficient - Regression Coefficient is the value that represents the change in the dependent variable Y for a unit change in the independent variable X.
Mean of X - Mean of X is the average value of all the data points in the variable X.

STEP 1: Convert Input(s) to Base Unit

Mean of Y: 200 --> No Conversion Required
Regression Coefficient: 5 --> No Conversion Required
Mean of X: 30 --> No Conversion Required

STEP 2: Evaluate Formula

Substituting Input Values in Formula

b₀ = ȳ-(b₁*x̅) --> 200-(5*30)

Evaluating ... ...

b₀ = 50

STEP 3: Convert Result to Output's Unit

50 --> No Conversion Required

FINAL ANSWER

50 <-- Regression Constant

(Calculation completed in 00.004 seconds)

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< 4 Regression Calculators

Simple Linear Regression Line

Go Dependent Random Variable Y = Regression Constant+(Regression Coefficient*Independent Random Variable X)

Regression Coefficient given Correlation

Go Regression Coefficient = Correlation between X and Y*(Standard Deviation of Y/Standard Deviation of X)

Regression Coefficient

Go Regression Coefficient = (Mean of Y-Regression Constant)/Mean of X

Regression Constant

Go Regression Constant = Mean of Y-(Regression Coefficient*Mean of X)

Regression Constant Formula

Regression Constant = Mean of Y-(Regression Coefficient*Mean of X)
b₀ = ȳ-(b₁*x̅)

What is Linear Regression?

Linear Regression is a statistical method used to model the relationship between a dependent variable (also known as the response variable) and one or more independent variables (also known as predictor variables). The goal of Linear Regression is to find the best-fitting line through a set of data points, which can then be used to make predictions about the response variable for different values of the predictor variables.
Linear Regression models are represented by the equation y = mx + b, where y is the response variable, x is the predictor variable, m is the slope of the line, and b is the y-intercept. Simple Linear Regression is used to model the relationship between one predictor variable and one response variable.
Linear Regression is a widely used statistical technique and is often used in fields such as economics, engineering, and the natural sciences.

How to Calculate Regression Constant?

Regression Constant calculator uses Regression Constant = Mean of Y-(Regression Coefficient*Mean of X) to calculate the Regression Constant, Regression Constant formula is defined as the intercept of the regression line on the Y-axis. It represents the expected value of Y when X is 0. Regression Constant is denoted by b₀ symbol.

How to calculate Regression Constant using this online calculator? To use this online calculator for Regression Constant, enter Mean of Y (ȳ), Regression Coefficient (b₁) & Mean of X (x̅) and hit the calculate button. Here is how the Regression Constant calculation can be explained with given input values -> 50 = 200-(5*30).

FAQ

What is Regression Constant?

Regression Constant formula is defined as the intercept of the regression line on the Y-axis. It represents the expected value of Y when X is 0 and is represented as b₀ = ȳ-(b₁*x̅) or Regression Constant = Mean of Y-(Regression Coefficient*Mean of X). Mean of Y is the average value of all the data points in the variable Y, Regression Coefficient is the value that represents the change in the dependent variable Y for a unit change in the independent variable X & Mean of X is the average value of all the data points in the variable X.

How to calculate Regression Constant?

Regression Constant formula is defined as the intercept of the regression line on the Y-axis. It represents the expected value of Y when X is 0 is calculated using Regression Constant = Mean of Y-(Regression Coefficient*Mean of X). To calculate Regression Constant, you need Mean of Y (ȳ), Regression Coefficient (b₁) & Mean of X (x̅). With our tool, you need to enter the respective value for Mean of Y, Regression Coefficient & Mean of X 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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