ALEX | Alabama Learning Exchange

Categorical Data Example

Classroom Resource Information

Title:

Categorical Data Example

URL:

https://www.khanacademy.org/math/statistics-probability/analyzing-categorical-data/two-way-tables-for-categorical-data/v/video-games-and-violence-bivariate-data

Content Source:

Other
Khan Academy

Type:

Audio/Video

Overview:

This video introduces students to the concept of bivariate categorical data. There are self-checking practice problems related to two-way frequency tables available.

Content Standard(s):

Mathematics
MA2019 (2019)
Grade: 9-12
Algebra I with Probability

32. Use mathematical and statistical reasoning with bivariate categorical data in order to draw conclusions and assess risk.

Example: In a clinical trial comparing the effectiveness of flu shots A and B, 21 subjects in treatment group A avoided getting the flu while 29 contracted it. In group B, 12 avoided the flu while 13 contracted it. Discuss which flu shot appears to be more effective in reducing the chances of contracting the flu.
Possible answer: Even though more people in group A avoided the flu than in group B, the proportion of people avoiding the flu in group B is greater than the proportion in group A, which suggests that treatment B may be more effective in lowering the risk of getting the flu.

	Contracted Flu	Did Not Contract Flu
Flu Shot A	29	21
Flu Shot B	13	12
Total	42	32

Unpacked Content

Evidence Of Student Attainment:

Students:
By using mathematical and statistical reasoning,

Draw conclusions about bivariate categorical data.
Assess risk related to bivariate categorical data

Teacher Vocabulary:

Quantitative lIteracy
Bivariate data
Categorical data
Risk

Knowledge:

Students know:

Key features of bivariate categorical data.
Strategies for drawing conclusions.
Strategies for assessing risk.

Skills:

Students are able to:

Analyze bivariate categorical data,
Draw conclusions from real-life bivariate categorical data,
Assess risk given real-life bivariate categorical data.

Understanding:

Students understand that:

Real-life situations often require drawing conclusions and assessing risk.
Quantitative literacy is important for making informed decisions.

Diverse Learning Needs:

Essential Skills:

Learning Objectives:
ALGI.32.1: Define proportional relationships, unit rate, and slope.
ALGI.32.2: Define probability of chance, outcomes and events.
ALGI.32.3: Define bivariate scatter plot, outlier, cluster, linear, nonlinear, and positive and negative association.
ALGI.32.4: Define relative frequency, bivariate, and frequency.
ALGl.32.5: Calculate frequency as it pertains to the data for a two-way table.

Prior Knowledge Skills:

Analyze scatter plots to determine line of best fit.
Define scatter plot, outlier, linear, quantitative, line of best fit, and variable.

Alabama Alternate Achievement Standards

AAS Standard:
M.A.AAS.11.32 Make predictions and draw conclusions from two variable data based on data displays and apply the results to a real-world situation.

Tags:

algebra I, bivariate categorical data, drawing conclusions, twoway frequency table

License Type:

Custom Permission Type
See Terms: https://www.khanacademy.org/about/tos
For full descriptions of license types and a guide to usage, visit :
https://creativecommons.org/licenses

Accessibility

Video resources: includes closed captioning or subtitles

Comments

This resource provided by:

Author:

Hannah Bradley

ALEX Classroom Resource

Categorical Data Example