← VCE Data Analysis

Purposes of qualitative and quantitative data

Quantitative data answers how many or how much questions with numbers; qualitative data explains why or how people feel. Using both gives a fuller picture.

Part of: VCE Applied Computing - U1O1 - Data analysis — Module 5, VCE Data Analytics - U3O2 - Analysis and Design — Module 60, ACARA Digital Technologies Years 9–10 — Acquiring and Validating Data — Module 11

Understanding Purposes of qualitative and quantitative data in VCE Data Analysis

What it does: The question asks how many, so quantitative data is needed. COUNTIF counts the number of yes responses. The rating is quantitative and the comment is qualitative. Together they show how satisfied users are and why. 'Why' and 'how people feel' questions are explained with opinions and comments, which is qualitative data. Qualitative data gives the reasons and feelings behind the numbers, usually as words. 'How much' asks for an amount, so numbers such as dollar values are needed. Feelings are best captured in words through interviews or open comments. Download counts only show how many. The percentage tells you how many. To learn why, you need qualitative data.

Common mistakes: Quantitative data answers 'how many' with numbers. The answer line should be a number such as 85, not a quote. A 'why' question needs qualitative data, which is explanations in people's own words. An average is a number, so it is quantitative.

Class: _____________________  ·  Name: _____________________  ·  Date: _________

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This module's key terms are also in a printable crossword (Modules 3–14) and word search (Modules 3–24).

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Learning
Duo
A school wants to know how many students bought lunch from the canteen this week. Which type of data answers this?
Quantitative dataQualitative data
Matches
Question: Why do students feel stressed? Data: =AVERAGE(C2:C50)
↓
A why question needs qualitative data, but the average of numbers only shows how much stress. It does not explain the reasons.
Applying
Meanings
Term
quantitative vs qualitative
Meaning
Quantitative data answers how many or how much questions with numbers; qualitative data explains why or how people feel. Using both gives a fuller picture.
Practice
How many students use the library? -> quantitative
Testing
Gaps
Data type:
Check Answer
Spots
3Method: count sales in sheet
4Answer: a quote from a buyer

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Quick Questions

1. A school wants to know how many students bought lunch from the canteen this week. Which type of data answers this?
A. Quantitative data ✓
B. Qualitative data
'How many' questions are answered with numbers, so quantitative data is the right choice.
2. A teacher wants to understand why Year 11 students feel stressed about SACs. Which type of data fits best?
A. Quantitative data
B. Qualitative data ✓
'Why' and 'how people feel' questions are explained with opinions and comments, which is qualitative data.
3. Which statement describes the purpose of quantitative data?
A. It measures how many or how much using numbers ✓
B. It explains why people feel the way they do
Quantitative data counts and measures. Explaining feelings and reasons is the purpose of qualitative data.
4. Which statement describes the purpose of qualitative data?
A. It explains why or how people feel using descriptions and opinions ✓
B. It measures how much using numbers only
Qualitative data gives the reasons and feelings behind the numbers, usually as words.
5. Research question: 'How much did the average household spend on electricity last quarter?' What is the best data type?
A. Qualitative data (written comments)
B. Quantitative data (dollar amounts) ✓
'How much' asks for an amount, so numbers such as dollar values are needed.

Match the Pairs

=AVERAGE(B2:B50) → Quantitative: gives a number that shows how much, such as the average hours of sleep
"Why did you stop using the app?" → Qualitative: an open question whose written answers explain reasons and feelings
Choosing the data type for the research question 'How many students buy lunch each day?' → =COUNTIF(C2:C100,"Yes")
Combining both types gives a fuller picture: the numbers show what happened and the comments explain why → Rating: 4/5 | Comment: "Easy to use"
Question: Why do students feel stressed? Data: =AVERAGE(C2:C50) → A why question needs qualitative data, but the average of numbers only shows how much stress. It does not explain the reasons.
Question: How many students own a laptop? Answer: "Lots of them" → A how many question needs quantitative data (a count or number), but the answer is a vague description.

Key Term

quantitative vs qualitative
Quantitative data answers how many or how much questions with numbers; qualitative data explains why or how people feel. Using both gives a fuller picture.

Fill in the Blanks

1. Question: How many students own a laptop? Data type: quantitative
Hint: Type the data type that answers 'how many' questions with numbers.
2. Question: Why do students dislike the app? Data type: qualitative
Hint: Type the data type that explains reasons and opinions.
3. Quantitative data is recorded as numbers
Hint: Type what form quantitative data takes when it is recorded.
4. Qualitative data explains how people feel
Hint: Type the word for what qualitative data reveals about people's opinions and emotions.
5. Using both types gives a fuller picture
Hint: Type the word describing how many data types are combined for a fuller picture.

Spot the Error

Question 1
A Question: How many sold?
B Type: quantitative
C Method: count sales in sheet
D Answer: a quote from a buyer
Line D — Quantitative data answers 'how many' with numbers. The answer line should be a number such as 85, not a quote.
Question 2
A Question: Why do users quit?
B Type: qualitative
C Method: interview 5 users
D Answer: an average of 4.2
Line D — A 'why' question needs qualitative data, which is explanations in people's own words. An average is a number, so it is quantitative.
Question 3
A Question: How much was spent?
B Type: qualitative
C Data: dollar amounts
D Result: total of $1250
Line B — 'How much' questions are answered with numbers, so the type should be quantitative, not qualitative.
Question 4
A Question: How do fans feel?
B Type: quantitative
C Method: open comments
D Result: feelings in words
Line B — Asking how people feel needs descriptive, qualitative data. It should say qualitative.
Question 5
A quantitative = how people feel
B qualitative = why, feelings
C both = fuller picture
Line A — Quantitative data answers how many or how much with numbers. How people feel is qualitative.

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