IB Digital Society Topic 3.1D Methods for Collecting and Organizing Data Revision Notes (SL/HL)

IB Digital Society Topic 3.1D Methods for Collecting and Organizing Data Revision Notes (SL/HL) | RevisionDojo

Written by official IB examiners

3.1D Methods for Collecting and Organizing Data

Collecting Data: Primary and Secondary

Primary data is collected firsthand for your own purpose (a survey you run, a sensor you set up). You control what is measured, but it costs time and effort.
Secondary data is collected by someone else and reused (a census, a published dataset). It is fast and cheap, but you did not control how it was collected, so it may not fit your question.
Most inquiries mix the two: a student on local transport might combine their own survey of classmates (primary) with published city ridership figures (secondary).

Exam technique

Exam technique

Primary data: you collected it, so you know its quality, though gathering it takes time and money. Secondary data is quicker and cheaper to grab, but it was collected for someone else's question and may not fit yours.
In the exam, name which type your real-world example uses, and why that matters.

Sampling: A Fair Slice of the Whole

You rarely collect from everyone, so you use a sample: a smaller group meant to stand in for the whole population.
A representative sample mirrors the population. One that over-represents some groups and misses others produces sampling bias, where results lean away from reality.
Online surveys make this vivid: a poll answered only by a platform's active users silently excludes everyone offline, busy, or uninterested.

Case study

Case study

System: the 1936 Literary Digest poll, early large-scale data collection using mailed surveys.
Specifics: 2.4 million responses predicted Landon would beat Roosevelt; Roosevelt won in a landslide.
Impacts and implications: the sample came from car and telephone owners, wealthier than average in the Depression, so the huge size hid deep bias. A big sample is not the same as a fair one.
Concepts: through systems, a small selection bias at collection propagated into a completely wrong output.

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Definition

Paywall

(on a website) an arrangement whereby access is restricted to users who have paid to subscribe to the site.

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Note

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam quis nostrud exercitation.

Excepteur sint occaecat cupidatat non proident

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Tip

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Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum.

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3.1D Methods for Collecting and Organizing Data

Collecting Data: Primary and Secondary

Primary data is collected firsthand for your own purpose (a survey you run, a sensor you set up). You control what is measured, but it costs time and effort.
Secondary data is collected by someone else and reused (a census, a published dataset). It is fast and cheap, but you did not control how it was collected, so it may not fit your question.
Most inquiries mix the two: a student on local transport might combine their own survey of classmates (primary) with published city ridership figures (secondary).

Exam technique

Exam technique

Primary data: you collected it, so you know its quality, though gathering it takes time and money. Secondary data is quicker and cheaper to grab, but it was collected for someone else's question and may not fit yours.
In the exam, name which type your real-world example uses, and why that matters.

Sampling: A Fair Slice of the Whole

You rarely collect from everyone, so you use a sample: a smaller group meant to stand in for the whole population.
A representative sample mirrors the population. One that over-represents some groups and misses others produces sampling bias, where results lean away from reality.
Online surveys make this vivid: a poll answered only by a platform's active users silently excludes everyone offline, busy, or uninterested.

Case study

Case study

System: the 1936 Literary Digest poll, early large-scale data collection using mailed surveys.
Specifics: 2.4 million responses predicted Landon would beat Roosevelt; Roosevelt won in a landslide.
Impacts and implications: the sample came from car and telephone owners, wealthier than average in the Depression, so the huge size hid deep bias. A big sample is not the same as a fair one.
Concepts: through systems, a small selection bias at collection propagated into a completely wrong output.

Definition

Paywall

(on a website) an arrangement whereby access is restricted to users who have paid to subscribe to the site.

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Note

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam quis nostrud exercitation.

Excepteur sint occaecat cupidatat non proident

Tip

Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum.

Topic 1 - Introduction - Digital Society1 subtopic

Topic 2 - Concepts - Digital Society7 subtopics

Topic 3 - Content - Digital Society7 subtopics

Topic 4 - Contexts - Digital Society7 subtopics

Topic 5 - Challenges and Interventions - Digital Society (HL)3 subtopics

IB Digital Society 3.1D Methods for Collecting and Organizing Data Notes

Topic 1 - Introduction - Digital Society1 subtopic

Topic 2 - Concepts - Digital Society7 subtopics

Topic 3 - Content - Digital Society7 subtopics

Topic 4 - Contexts - Digital Society7 subtopics

Topic 5 - Challenges and Interventions - Digital Society (HL)3 subtopics

3.1D Methods for Collecting and Organizing Data

Collecting Data: Primary and Secondary

Sampling: A Fair Slice of the Whole

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Excepteur sint occaecat cupidatat non proident

Unlock the rest of this chapter with a free account

3.1D Methods for Collecting and Organizing Data

Collecting Data: Primary and Secondary

Sampling: A Fair Slice of the Whole

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Excepteur sint occaecat cupidatat non proident

Unlock the rest of this chapter with a free account