Weather Data Analysis and Patterns

Weather Data Analysis and Patterns

Assessment

Interactive Video

Science

6th - 8th Grade

Hard

Created by

Patricia Brown

FREE Resource

The video tutorial covers lesson 6.1 on weather patterns, focusing on identifying and analyzing patterns in weather data. It explains how meteorologists use past and current data to predict weather, and guides students through analyzing weather maps and symbols. The lesson includes procedures for data analysis, emphasizing the importance of detailed observations before, during, and after a storm. Students are encouraged to reflect on surprising data patterns and complete related activities.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary focus of lesson 6.1 in the weather change tutorial?

Understanding cloud formation

Identifying patterns in data

Studying ocean currents

Learning about climate zones

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How do meteorologists use patterns to predict the weather?

By observing animal behavior

By analyzing past and current patterns

By measuring soil moisture

By tracking ocean tides

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What do the colors green, yellow, and orange indicate on a weather map?

Humidity

Precipitation

Temperature

Wind speed

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are troughs on a weather map?

Areas of high pressure

Zones of strong winds

Elongated areas of low pressure

Regions of high humidity

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the significance of drawing lines on weather data graphs?

To highlight temperature changes

To separate data into time periods

To mark areas of high pressure

To indicate wind direction

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What should students record in their data tables during the analysis?

Cloud types

Wind speed and direction

Observations of all weather conditions

Only temperature changes

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of dividing data into before, during, and after storm periods?

To focus on temperature only

To simplify data entry

To identify patterns and changes

To exclude irrelevant data

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