Understanding Categorical Data and Associations

The video tutorial explores how to handle categorical data, using two-way tables to analyze relationships between categories. It demonstrates how to fill in missing values and convert data into percentages for better understanding. The tutorial also covers visualizing data with graphs, such as bar charts, to identify patterns and associations. It concludes by analyzing whether certain categories are connected, using examples like snowmobiles and skateboards, and deciduous versus evergreen trees.

What type of data is best represented using two-way tables?

• Discrete data

• Continuous data

• Categorical data

• Numerical data

What is an example of categorical data mentioned in the video?

• Weight in kilograms

• Hair color

• Age in years

• Height in centimeters

Tags

CCSS.8.SP.A.4

In a two-way table, if you know the total number of students who passed, how can you find the number who passed and studied?

• Divide the total by the number who studied

• Subtract the number who failed from the total

• Add the number who studied to the total

• Subtract the number who passed but did not study from the total

Tags

CCSS.2.OA.A.1

If 34 students passed and studied, and 38 total studied, how many studied and failed?

• 4

• 6

• 10

• 34

Tags

CCSS.7.SP.A.2

Why might it be useful to convert data into percentages?

• To make the data more complex

• To simplify calculations

• To increase the data size

• To better understand relationships between categories

Tags

CCSS.8.SP.A.4

What percentage of people who like snowmobiles also like skateboards?

• 18%

• 76%

• 24%

• 82%

What does a segmented bar graph represent?

• A hundred total divided into parts

• A scatterplot of data points

• A single category

• A pie chart of percentages

Tags

CCSS.8.SP.A.4

How can you determine if there is an association between two categories using a bar graph?

• By measuring the width of the bars

• By counting the number of bars

• By looking for a big difference in the bar heights

• By checking if the bars are the same color

Tags

CCSS.8.SP.A.4

In the example of tree height, what was concluded about the association between tree type and height?

• There was a strong association

• Deciduous trees were shorter

• There was no association

• Evergreen trees were taller

Tags

CCSS.RI.6.7

CCSS.RI.8.7

CCSS.RI.9-10.7

CCSS.RL.6.7

CCSS.RL.7.7

What was the conclusion about the relationship between meditation and calmness?

• Meditation increased calmness

• Meditation decreased calmness

• No association was found

• Calmness was unrelated to meditation

Tags

CCSS.RI.6.7

CCSS.RI.8.7

CCSS.RI.9-10.7

CCSS.RL.6.7

CCSS.RL.9-10.7