Recent questions in Regression Analysis

Inferential StatisticsAnswered question

Brandon White 2022-11-24

Can the original function be derived from its ${k}^{th}$ order Taylor polynomial?

Inferential StatisticsAnswered question

ajakanvao 2022-11-23

Should the independent (or dependent) variables in a linear regression model be normal or just the residual?

Inferential StatisticsAnswered question

ajumbaretu 2022-11-20

What is the benefit of OU vs regression for modeling data, say data in the form of ($x,y$) pairs?

Inferential StatisticsAnswered question

Laila Murphy 2022-11-20

What kind of technique is to be adopted if I have to find an equation or model for say, $D$ depends on $C$, $C$ changes for a set of $B$, which changes for different $A$.

Inferential StatisticsAnswered question

Kale Sampson 2022-11-19

From numerical simulation and regression analysis I discovered that the root-mean-square amplitude of white noise with bandwidth $\mathrm{\Delta}\phantom{\rule{negativethinmathspace}{0ex}}f$ is proportional to $\sqrt{\phantom{\rule{negativethinmathspace}{0ex}}\mathrm{\Delta}\phantom{\rule{negativethinmathspace}{0ex}}f}$. How can this be derived mathematically ?

Inferential StatisticsAnswered question

Yaretzi Mcconnell 2022-11-19

How can one find the root of sesquilinear form with positive definite matrix?

Inferential StatisticsAnswered question

Kayley Dickson 2022-11-18

In a Simple Linear Regression analysis, independent variable is weekly income and dependent variable is weekly consumption expenditure. Here $95$% confidence interval of regression coefficient, ${\beta}_{1}$ is $(.4268,.5914)$.

Inferential StatisticsAnswered question

Adison Rogers 2022-11-17

How to find AIC values for both models using $R$ software?

Inferential StatisticsAnswered question

Bayobusalue 2022-11-12

Are the ordinary least squares regression coefficients uniformly integrable?

Inferential StatisticsAnswered question

Aryanna Fisher 2022-11-12

Is it always true that

$det({A}^{T}A)=0$ , for $A=n\times m$ matrix with $n<m$?

$det({A}^{T}A)=0$ , for $A=n\times m$ matrix with $n<m$?

Inferential StatisticsAnswered question

Fahdvfm 2022-11-12

Find a regression to this : $a\equiv t\phantom{\rule{0.444em}{0ex}}(\mathrm{mod}\phantom{\rule{0.333em}{0ex}}\mathrm{\Delta})$, $a$ and $\mathrm{\Delta}$ are the unknowns constants.

Inferential StatisticsAnswered question

Annie French 2022-11-11

Is it a "standard" Math/Numerical-Analysis hack to add a relatively small number e.g. 1*10E-5 to the diagonal of a squared matrix to ensure LU Decomposition (or whichever decomposition algorithm is applicable)? As opposed to "partially/totally pivoting"?

Inferential StatisticsAnswered question

Siena Erickson 2022-11-11

What is degree of freedom in statistics?

Inferential StatisticsAnswered question

Mark Rosales 2022-11-11

How can we fit a set of data points to a hyperbola, a square root function or a logarithmic function?

Inferential StatisticsAnswered question

Yaretzi Mcconnell 2022-11-09

What is the meaning of :$:s$ after a mathematical symbol?

Inferential StatisticsAnswered question

Kale Sampson 2022-11-09

Whether there is some connection between fitting probability distribution on some data set and linear regression? Or this two tools are for different problems?

Inferential StatisticsAnswered question

klasyvea 2022-11-06

What are the prerequisites for regression analysis?

Inferential StatisticsAnswered question

Jaslyn Sloan 2022-11-05

Find the function that describes a real life curve

Inferential StatisticsAnswered question

Nola Aguilar 2022-11-05

Principal Component Analysis - linear or nonlinear relationships between variables?

Inferential StatisticsAnswered question

kaltEvallwsr 2022-11-03

Can we determine if two random variables are independent if I know their expected values and the variances?

- 1
- 2

Regression analysis is an invaluable tool for data analysis. It allows for the estimation of relationships between independent and dependent variables, as well as for the prediction of future values. Linear regression analysis is the most commonly used type of regression analysis, and is used to assess the strength of the linear relationship between two variables. The regression analysis formula is a mathematical equation which can be used to calculate the regression coefficient. Regression analysis examples are everywhere: from finance, to economics, to science, to engineering, and more. Using equations, you can use regression analysis to find answers to some of the most complex questions. If you need help with regression analysis, Plainmath available to help you!