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Linear Regression Coefficient Calculator

Linear Regression Slope Formula:

\[ b = \frac{n \sum(xy) - \sum x \sum y}{n \sum(x^2) - (\sum x)^2} \]

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1. What is Linear Regression Coefficient?

The linear regression coefficient (slope) measures the relationship between two variables in a linear regression model. It represents how much the dependent variable (y) changes for each unit change in the independent variable (x).

2. How Does the Calculator Work?

The calculator uses the linear regression slope formula:

\[ b = \frac{n \sum(xy) - \sum x \sum y}{n \sum(x^2) - (\sum x)^2} \]

Where:

Explanation: The formula calculates the best-fit line slope that minimizes the sum of squared errors between observed and predicted values.

3. Importance of Slope Coefficient

Details: The slope coefficient is fundamental in statistical analysis, helping to understand relationships between variables, make predictions, and test hypotheses in various fields including economics, science, and social research.

4. Using the Calculator

Tips: Enter x and y values as comma-separated numbers. Both arrays must have the same number of values. Ensure data represents a linear relationship for meaningful results.

5. Frequently Asked Questions (FAQ)

Q1: What does a positive slope indicate?
A: A positive slope indicates a positive relationship - as x increases, y tends to increase.

Q2: What does a negative slope indicate?
A: A negative slope indicates an inverse relationship - as x increases, y tends to decrease.

Q3: How is slope different from correlation?
A: Slope measures the rate of change, while correlation measures the strength and direction of the linear relationship.

Q4: What is the range of possible slope values?
A: Slope can be any real number from negative to positive infinity, depending on the data relationship.

Q5: When is slope undefined?
A: Slope is undefined when all x values are identical (zero variance in x), causing division by zero in the denominator.

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