onlineregression11:   One-predictor-variable linear regression   ⇒   y = f(x)

Formulas

β = [Σ(xy)-(ΣxΣy)/n]/{Σ(x2)-[(Σx)2/n]}

α = [Σy-(βΣx)]/n

Reference

Ponce, V. M. 1989. Engineering Hydrology, Principles and Practices. Prentice Hall, pages 239-241.
Example
INPUT DATA:

Enter array size n:     

Enter paired values of arrays y and x (separate each value with a comma; maximum string length is 300 characters).

y:     

x:     

ECHO OF INPUT:

n =  

y(1) =  .   

x(1) =  .   

OUTPUT:

α =       β =       standard deviation sx =       standard deviation sy =

Correlation coeficient r =       standard error of estimate se =

            

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online calc
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C1 wsprofile H2 wsprofile A2 wsprofile C3 wsprofile H3 wsprofile A3 wsprofile
sequent depth HJ energy loss HJ initial sequent HJ efficiency HJ critical width constriction
ogee spillway Hazen-Williams parallel pipes three reservoirs tractive force
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Gumbel Gumbel 2 Log Pearson Log Pearson 2 TR-55 graphical curve number
Overland flow using the diffusion wave method Dynamic hydraulic diffusivity convolution S-hydrograph time of concentration water balance
UH cascade dimensionless UH cascade general UH cascade series UH cascade all series UH cascade
one-predictor linear one-predictor nonlinear two-predictor linear two-predictor nonlinear hyperbolic regression
fall velocity Lane & Koelzer USLE USLE2 Dendy-Bolton Shields
Duboys Meyer-Peter Colby 1957 Colby reservoir design life Equilibrium channel top width using the Lane et al. theory
Modified Einstein Procedure bridge scour using Melville equation
DO sag DO sag analysis Oxygenation Salinity (EC to TDS)