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What are the problems attached with non normal data in regression?
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What is the statistical study of the relationship between two sets of data?
Regression.
What does it mean to say that a data point has a residual of -1?
The point lies 1 unit below the regression line.
When using the Regression tools you cannot plot the points of your data and your model on the same graph?
False
is it possible to use primary data as independent variable and secondary data as independent variable in correlation analysis and regression analysis?
Possible maybe
What are the advantages and disadvantage of logistic regression compared with linear regression analysis?
It all depends on what data set you're working with. There a quite a number of different regression analysis models that range the gambit of all functions you can think of. Obviously some are more useful than others. Logistic regression is extremely useful for population modelling because population growth follows a logistic curve. The final goal for any regression analysis is to have a mathematical function that most closely fits your data, so advantages and disadvantages depend entirely upon that.
In a regression of a time series that states data as a function of calendar year what requirement of regression is violated?
In a regression of a time series that states data as a function of calendar year, what requirement of regression is violated?
How does Logistic regression Work?
The logistic regression "Supervised machine learning" algorithm can be used to forecast the likelihood of a specific class or occurrence. It is used when the result is binary or dichotomous, and the data can be separated linearly. Logistic regression is usually used to solve problems involving classification models. For more information, Pls visit the 1stepgrow website.
What has the author MH Pesaran written?
M.H Pesaran has written: 'Dynamic regression' -- subject(s): Regression analysis, Data processing
If the coefficient of determination for a data set containing 12 points is 0.5 6 of the data points must lie on the regression line for the data set.?
That is not true. It is possible for a data set to have a coefficient of determination to be 0.5 and none of the points to lies on the regression line.
Is the line of best fit the same as linear regression?
Linear Regression is a method to generate a "Line of Best fit" yes you can use it, but it depends on the data as to accuracy, standard deviation, etc. there are other types of regression like polynomial regression.
What is the statistical study of the relationship between two sets of data?
Regression.
Is multiple regression a quantitative data anaysis?
Not necessarily. Qualitative data could be coded to enable such analysis.
What Is a Logistic Regression Algorithm?
Using real-world data from a data set, a statistical analysis method known as logistic regression predicts a binary outcome, such as yes or no. A logistic regression model forecasts a dependent data variable by examining the correlation between one or more existing independent variables. Please visit for more information 1stepgrow.
What is the normal probability plot of residuals?
When you use linear regression to model the data, there will typically be some amount of error between the predicted value as calculated from your model, and each data point. These differences are called "residuals". If those residuals appear to be essentially random noise (i.e. they resemble a normal (a.k.a. "Gaussian") distribution), then that offers support that your linear model is a good one for the data. However, if your errors are not normally distributed, then they are likely correlated in some way which indicates that your model is not adequately taking into consideration some factor in your data. It could mean that your data is non-linear and that linear regression is not the appropriate modeling technique.
The ability to breakdown data and see how various elements fit with each other and the way they relate to other elements?
Sounds like you are talking about a regression or regression analysis.
What is the line that most clearly fits a set of data called in math?
A regression line.
In a Quadratic Regression problem a graph is a perfect fit for the data when r?
r = 0
