Interpreting Scatterplots and Outliers

Interpreting Scatterplots and Outliers

Assessment

Interactive Video

Mathematics

9th - 10th Grade

Hard

Created by

Thomas White

FREE Resource

The video tutorial covers interpreting scatterplots by focusing on four key aspects: direction, form, strength, and unusual features. It explains how to identify positive or negative associations, recognize linear or nonlinear patterns, assess the strength of relationships, and spot outliers. The tutorial also highlights common mistakes students make in assignments, particularly in identifying and describing outliers.

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15 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the four key aspects to consider when interpreting scatterplots?

Slope, Intercept, Residuals, Outliers

Correlation, Causation, Variation, Deviation

Mean, Median, Mode, Range

Direction, Form, Strength, Unusual Features

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is NOT a key aspect of interpreting scatterplots?

Strength

Direction

Color

Form

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a positive association in a scatterplot indicate?

The variables are inversely proportional

As one variable increases, the other also increases

There is no relationship between the variables

As one variable increases, the other decreases

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What type of association is present if the scatterplot shows that as one variable decreases, the other also decreases?

Positive association

Inverse association

Negative association

No association

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which pattern is typically expected in the form of data in scatterplots?

Linear

Circular

Exponential

Random

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which form of data is NOT typically expected in scatterplots?

Circular

Random

Nonlinear

Linear

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main focus when analyzing the form of data in scatterplots?

Counting the number of data points

Determining if the pattern is linear or nonlinear

Measuring the distance between points

Identifying the color of data points

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