SHS3 Additional Mathematics · Semester 2, Week 9
Organising and Representing and Interpreting Data
Full lesson notes coming
Notes for this lesson are being prepared. The curriculum details below are complete and ready to use for your planning.
Curriculum details
- Strand
- Handling Data (Strand 4)
- Sub-strand
- Organising and Representing and Interpreting Data (4.1)
- Content standard
- 3.4.1.CS.1 - Demonstrate understanding of the nature and strength of relationship between two given variables. 3.4.1.LO.1 Describe the nature and strength of relationship between two given variables using scatter diagram and correlation coefficient. 3.4.1.LO.2 Model and solve problems using regression analysis.
- Indicator
- 3.4.1.LI.1 - Distinguish between univariate and bivariate data and give examples and explain the concept of correlation.
- Suggested placement
-
Semester 2, Week 9
(Week 29 of the year)
Our suggestion, laid out in curriculum order across three terms of twelve weeks. NaCCA does not fix the week, so follow your school's scheme of learning.
- Curriculum reference
- NaCCA curriculum document, p. 539
Exemplars (from the NaCCA curriculum)
Think-pair-share, Experiential Learning; and Group Work/Collaborative Learning. Learning Experience: Learners in groups discuss correlation. Activity 1: The Idea of Correlation Learners provide examples of univariate data they are familiar with and brainstorm on bivariate data. Learners share their ideas on the concept and the use of correlation. - Univariate means one variable (one type of data) and bivariate means two variables (two types of data). - With bivariate data we have two sets of related data we want to compare. Examples of Univariate data: Age of students, height of students, travel time etc. - With univariate data, you can find the central value using mean, median and mode or find how spread out the data is using range, quartiles and standard deviation. However, this form of analysis gives only just simple explanation because only one quantity is used, unlike bivariate data. - With univariate data you can make plots like bar graphs, pie charts and histogram. Examples of bivariate data: Age of students and their height, price of goods and quantities of goods, hours students spend studying and their test scores. Bivariate data can be used to more comparison. Teaching and Learning Resources: - ICT tools - Calculators - SHS curriculum Assessment (3.4.1.AS.1). The document marks these depth-of-knowledge levels for this indicator: Level 1 Recall; Level 2 Skills of conceptual understanding.