Graph Interpretation and Misleading Data

Graph Interpretation and Misleading Data

Assessment

Interactive Video

Mathematics

9th - 10th Grade

Hard

Created by

Patricia Brown

FREE Resource

The video tutorial focuses on interpreting graphs, highlighting the importance of titles, axes, and scales. It provides examples of misleading graphs, such as those related to voting and A-Level exams, and explains how dual scales and image scaling can mislead viewers. The tutorial emphasizes careful analysis to avoid being tricked by visual data representations.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is it important for a graph to have a title?

To make it look more professional

To increase the size of the graph

To ensure the graph is colorful

To clarify what the graph is explaining

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What should be labeled on a graph to help understand the data?

The font style

The border

The axes

The background color

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the context of graphs, what does the term 'scale' refer to?

The intervals of numbers on the axes

The type of graph used

The color of the graph

The size of the graph

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was misleading about the 'vote line' graph example?

The graph had no title

The colors were incorrectly associated with the data

The graph was too small

The graph used the wrong type of chart

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the UK graph example, what was a major issue?

The graph had missing data

The graph was too large

The graph was too colorful

The graph used the wrong font

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a common issue with graphs that use different scales?

They are easier to read

They can mislead by making data appear comparable

They are more accurate

They are more colorful

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can different scales on a graph be misleading?

They make the graph look more interesting

They can make data sets appear similar when they are not

They make the graph easier to understand

They increase the size of the graph

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