Identifying Misleading Graphs

Identifying Misleading Graphs

Assessment

Interactive Video

Science

6th - 10th Grade

Easy

NGSS
HS-ESS3-5, HS-ETS1-3

Standards-aligned

Created by

Aiden Montgomery

Used 24+ times

FREE Resource

Standards-aligned

NGSS.HS-ESS3-5
,
NGSS.HS-ETS1-3
The video discusses how graphs can be used to mislead and manipulate data presentation. It highlights common techniques such as scale distortion, cherry picking, and data omission. Examples include a Chevy ad and unemployment data. The video emphasizes the importance of critically analyzing graphs by examining labels, numbers, scales, and context to understand the true story behind the data.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why might we not question exaggerated claims in advertising and politics?

Because they are backed by science

Because they are rare

Because we are used to them

Because they are always true

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a graph represent?

Cold, hard numbers

Speculations

Assumptions

Opinions

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the 1992 Chevy ad, what was misleading about the graph?

It used too many colors

It showed irrelevant information

It distorted the y-axis scale

It used incorrect data

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can zooming in on a small portion of the y-axis mislead viewers?

By hiding the data

By making differences seem larger than they are

By making the graph colorful

By changing the data

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a common way to distort data in line graphs?

Using 3D effects

Adding irrelevant data

Distorting the x-axis scale

Using too many colors

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does 'cherry picking' data involve?

Using random data points

Using all available data

Selecting data that supports a specific narrative

Ignoring all data

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why might a graph showing Super Bowl viewership be misleading?

It uses incorrect data

It uses too many colors

It doesn't account for population growth

It shows irrelevant data

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