least squares regression line

least squares regression line

Assessment

Flashcard

Mathematics

11th - 12th Grade

Hard

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15 questions

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1.

FLASHCARD QUESTION

Front

What is the least squares regression line?

Back

The least squares regression line is a statistical method used to determine the line of best fit for a set of data points by minimizing the sum of the squares of the vertical distances (residuals) between the observed values and the values predicted by the line.

2.

FLASHCARD QUESTION

Front

What does a correlation coefficient (r) of 0.8 indicate?

Back

A correlation coefficient (r) of 0.8 indicates a strong positive linear relationship between two variables.

3.

FLASHCARD QUESTION

Front

What does it mean if two variables are correlated?

Back

If two variables are correlated, it means that there is a statistical relationship between them, indicating that changes in one variable are associated with changes in the other.

4.

FLASHCARD QUESTION

Front

What does random scatter in the residuals indicate about a regression model?

Back

Random scatter in the residuals indicates that a linear model is appropriate for the data, suggesting that the model captures the relationship well without systematic errors.

5.

FLASHCARD QUESTION

Front

What does a correlation coefficient near 1 or -1 signify?

Back

A correlation coefficient near 1 signifies a strong positive linear relationship, while a coefficient near -1 signifies a strong negative linear relationship between two variables.

6.

FLASHCARD QUESTION

Front

How does changing the units of measurement for x or y affect the correlation coefficient?

Back

Changing the units of measurement for x or y does not change the correlation coefficient; it remains the same regardless of the units used.

7.

FLASHCARD QUESTION

Front

What is a residual plot?

Back

A residual plot is a graphical representation of the residuals (the differences between observed and predicted values) plotted against the independent variable or predicted values, used to assess the fit of a regression model.

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