Cubic Regression Lite
Basic Regression
免費
1.0for iPhone, iPad
Age Rating
Cubic Regression Lite 螢幕截圖
About Cubic Regression Lite
There are two Cubic regression calculators:
1. The standard Cubic regression calculator.
2. The Cubic regression calculator with predicted value.
This version can handle up to 12 sets of data.
They cover the Cubic regression equation, the Quadratic and Linear regression equations(for reference only).
Cubic regression equation function has the form:
y = a + bx + cx² + dx³
where a, b, c, d are called the coefficient of the cubic regression model.
If d = 0, y = a + bx + cx², it will have the dataset with U shape pattern.
If c = 0 and d = 0, y = a + bx , it will have the dataset with linear shape pattern.
If the dataset does not fall into the perfect linear or the parabolic pattern, it will be more appropriate to use the Cubic regression equation.
It is useful in various fields, such as:
finance, physics, engineering, and social sciences, where there have nonlinear relationships between variables.
Note: we need to stick the value of predicted value of x lies within the minimum and maximum values of array of x data.
Together with the linear and quadratic regression equations, it is a great tool to visualize the whole picture of the dataset analysis.
Highlighted features are:
1. A short learning curve.
2. Showing all equations with options for comparison.
3. Data will be rearranged in ascending order internally.
4. An unique data entry method with error detection.
5. A well formatted chart with options for different selections.
6. Results can be emailed.
7. It can handle 40 sets of data. (for standard version)
1. The standard Cubic regression calculator.
2. The Cubic regression calculator with predicted value.
This version can handle up to 12 sets of data.
They cover the Cubic regression equation, the Quadratic and Linear regression equations(for reference only).
Cubic regression equation function has the form:
y = a + bx + cx² + dx³
where a, b, c, d are called the coefficient of the cubic regression model.
If d = 0, y = a + bx + cx², it will have the dataset with U shape pattern.
If c = 0 and d = 0, y = a + bx , it will have the dataset with linear shape pattern.
If the dataset does not fall into the perfect linear or the parabolic pattern, it will be more appropriate to use the Cubic regression equation.
It is useful in various fields, such as:
finance, physics, engineering, and social sciences, where there have nonlinear relationships between variables.
Note: we need to stick the value of predicted value of x lies within the minimum and maximum values of array of x data.
Together with the linear and quadratic regression equations, it is a great tool to visualize the whole picture of the dataset analysis.
Highlighted features are:
1. A short learning curve.
2. Showing all equations with options for comparison.
3. Data will be rearranged in ascending order internally.
4. An unique data entry method with error detection.
5. A well formatted chart with options for different selections.
6. Results can be emailed.
7. It can handle 40 sets of data. (for standard version)
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最新版本1.0更新日誌
Last updated on 2023年07月07日
Version History
1.0
2023年07月07日
Cubic Regression Lite FAQ
點擊此處瞭解如何在受限國家或地區下載Cubic Regression Lite。
以下為Cubic Regression Lite的最低配置要求。
iPhone
須使用 iOS 16.0 或以上版本。
iPad
須使用 iPadOS 16.0 或以上版本。
Cubic Regression Lite支持英文
