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What is the exponential model formula?

ŷ = abˣ

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What is the exponential model formula?

ŷ = abˣ

What is the transformed exponential model formula?

ln(ŷ) = ln(a) + ln(b)x

What is the power model formula?

ŷ = axᵇ

What is the transformed power model formula?

ln(ŷ) = ln(a) + bln(x)

How to calculate 'a' in the original exponential model after transformation?

a = e^a* (where a* is the y-intercept of the transformed LSRL)

How to calculate 'b' in the original exponential model after transformation?

b = e^b* (where b* is the slope of the transformed LSRL)

How to calculate 'a' in the original power model after transformation?

a = e^a* (where a* is the y-intercept of the transformed LSRL)

How to calculate 'b' in the original power model after transformation?

b = b* (where b* is the slope of the transformed LSRL)

Explain the impact of outliers on a regression model.

Outliers can drastically reduce the correlation and may change the y-intercept of the regression line.

Explain the impact of high-leverage points on a regression model.

High-leverage points can significantly change the slope and may change the y-intercept of the regression line.

Explain how to transform data for an exponential model.

Take the natural logarithm (ln) of the y-values to linearize the relationship between ln(y) and x.

Explain how to transform data for a power model.

Take the natural logarithm (ln) of both the x and y-values to linearize the relationship between ln(y) and ln(x).

Explain how residual plots help in assessing model fit.

A random scatter of points in the residual plot indicates a good fit. Patterns suggest the model is not appropriate.

Explain the meaning of R² value.

R² represents the percentage of variation in the response variable explained by the model. Higher R² generally indicates a better fit.

What are the differences between outliers and high-leverage points?

Outliers: y-value far from the regression line, large residual | High-Leverage Points: x-value far from other points, potentially changes slope.

What are the differences between exponential and power model transformations?

Exponential: ln(y) vs. x | Power: ln(y) vs. ln(x)

What are the differences between the effects of outliers vs high leverage points?

Outliers: Affect correlation and y-intercept more | High Leverage Points: Affect the slope more

What are the differences between interpreting 'b' in transformed exponential and power models?

Exponential: b* needs to be exponentiated (e^b*) to find original 'b' | Power: b* is the original 'b'

What are the differences between the original exponential and power models?

Exponential: ŷ = abˣ (y changes exponentially with x) | Power: ŷ = axᵇ (y changes by a power of x)