SHS1 Mathematics · Semester 2, Week 11
Statistical Reasoning and Its Application in Real Life
Lesson notes
Learning Objectives
Indicator: 1.4.1.LI.1 - Classify data (primary and secondary) as quantitative (discrete and continuous), qualitative (nominal and ordinal), numerical, categorical, grouped, ungrouped, etc.
By the end of the lesson, learners can:
- Distinguish between primary and secondary data, giving at least two authentic examples of each.
- Classify a given set of data as quantitative (discrete or continuous) or qualitative (nominal or ordinal) with justification.
- Explain the difference between grouped and ungrouped data and identify when each form is appropriate.
- Sort data cards under given headings and justify their reasoning using the correct statistical terminology.
- Identify the type of data used in a short real-life document (e.g., a newspaper report or market record) and give reasons for their classification.
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Sign in with phone numberCurriculum details
- Strand
- Making Sense of and Using Data (Strand 4)
- Sub-strand
- Statistical Reasoning and Its Application in Real Life (4.1)
- Content standard
- 1.4.1.CS.1 - Demonstrate a conceptual understanding of the appropriateness of data collection methods to collect everyday life data. 1.4.1.LO.1 Decide whether or not a selected data collection method is appropriate given a particular data, justify responses, and collect both qualitative and quantitative data with the appropriate methods.
- Indicator
- 1.4.1.LI.1 - Classify data (primary and secondary) as quantitative (discrete and continuous), qualitative (nominal and ordinal), numerical, categorical, grouped, ungrouped, etc.
- Suggested placement
-
Semester 2, Week 11
(Week 31 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. 133
Exemplars (from the NaCCA curriculum)
Using project-based learning activities, learners research and make presentations on primary data (gathered by the researcher himself, e.g., surveys, interviews, experiments, etc.) and secondary data (collected by someone else earlier). Example 1: Using data hunting game, write a variety of data types on different cards and task learners to sort the cards under given headings and justify their reason for the sorting. Using project-based learning activities, engage learners to research a number of existing documents on/from the internet/textbooks/magazines/newspapers and describe, with reasons, the type of data used. Example 1: Discuss and draw out the differences, with examples, between discrete and continuous data. Hint: 1. Discrete data includes discrete variables that are finite, numeric, countable, and non-negative integers. E.g.: i. The number of students who have attended the class. ii. The number of customers who have bought different products. iii. The number of groceries people are purchasing every day. Hint 2. Continuous data is the unspecified number of possible measurements between two presumed points. - The weather temperature. - The wind speed. - The weight of the kids. Using project-based learning activities, task learners to research and make presentations on the importance of grouped and ungrouped data, discrete and continuous data, etc. in the areas of marketing and advertising, research, population analysis, etc. Teaching and Learning Resources: - Sample questionnaire - interview guides - observation guide - Computer-assisted telephone interview guide - mail survey Assessment (1.4.1.AS.1). The document marks these depth-of-knowledge levels for this indicator: Level 1 Recall; Level 2 Skills of conceptual understanding; Level 3 Strategic reasoning.