Linear Regression Flashcard

Linear Regression Flashcard

Assessment

Flashcard

Mathematics

12th Grade

Practice Problem

Hard

CCSS
HSS.ID.B.5, 8.EE.B.5, 8.SP.A.2

+10

Standards-aligned

Created by

Wayground Content

FREE Resource

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15 questions

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1.

FLASHCARD QUESTION

Front

What is linear regression?

Back

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

Tags

CCSS.8.SP.A.2

2.

FLASHCARD QUESTION

Front

What does the correlation coefficient (r) indicate?

Back

The correlation coefficient (r) measures the strength and direction of a linear relationship between two variables, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation).

Tags

CCSS.HSS.ID.C.8

3.

FLASHCARD QUESTION

Front

What does a weak negative correlation mean?

Back

A weak negative correlation indicates that as one variable increases, the other variable tends to decrease slightly, but the relationship is not strong.

Tags

CCSS.HSS.ID.B.5

4.

FLASHCARD QUESTION

Front

What is the equation of the line of best fit?

Back

The equation of the line of best fit is a linear equation that best represents the data points in a scatter plot, typically expressed in the form y = mx + b, where m is the slope and b is the y-intercept.

Tags

CCSS.8.EE.B.5

5.

FLASHCARD QUESTION

Front

How do you calculate the slope (m) in linear regression?

Back

The slope (m) in linear regression is calculated using the formula: m = (NΣ(xy) - ΣxΣy) / (NΣ(x^2) - (Σx)^2), where N is the number of data points.

Tags

CCSS.8.EE.B.5

6.

FLASHCARD QUESTION

Front

What is the significance of the y-intercept (b) in a linear equation?

Back

The y-intercept (b) is the value of the dependent variable when the independent variable is zero, representing the starting point of the line on the y-axis.

Tags

CCSS.8.EE.B.6

CCSS.8.F.A.3

7.

FLASHCARD QUESTION

Front

What does it mean if r = 0?

Back

If r = 0, it indicates that there is no linear correlation between the two variables, meaning changes in one variable do not predict changes in the other.

Tags

CCSS.HSS.ID.B.5

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