Grade 7
MATATAG
Types of
OBJECTIVES
• understand the importance of data
collection
• identify the types of data
Focus
Questions
Have you ever counted something or looked for
patterns before?
Have you ever kept track of your grades to see
if you're improving? What did you notice?
Imagine your teacher is choosing a theme for a
class party. How could your teacher find out
which theme everyone likes the most?
Have you ever thought about how companies
know which products are popular or how
YouTube recommends videos for you?
Statistics
Statistics is a branch of mathematics that involves
collecting, organizing, analyzing, and interpreting
data to help us make informed decisions.
Data
Data refers to information such as facts and numbers
used to analyze something or to make decision.
It can come in various forms, such as numbers, words,
measurements, or observations, and is often used to
gain insights, answer questions, or solve a problem.
Importance
of Data
Importance of Data
Helps Us Make Decisions
Data provides the information we
need to make better choices.
EXAMPLES:
PAGASA provides weather
forecasts to help people
make decisions about their
daily activities.
Importance of Data
Reveals Patterns and Trends
Data allows us to see what happens
often or changes over time.
EXAMPLES:
A sports team might notice that they
perform better in games after a
particular type of practice.
Importance of Data
Supports Fairness and Accuracy
Data ensures decisions are
based on facts, not guesses.
EXAMPLES:
Fake news spreads
false information, but
accurate data helps
us uncover the truth.
Importance of Data
Solves Problems
Data helps us find solutions by
understanding the problem better.
EXAMPLES:
A city might use traffic data
to decide where to build a new
road to reduce congestion.
Importance of Data
Used Everywhere
Data is essential in school, business,
medicine, sports, and technology.
EXAMPLES:
Doctors use medical data to
diagnose illnesses, while
companies use sales data to
improve their products.
Types of
Data
Qualitative Data
• Qualitative data describes qualities, characteristics, or
categories and cannot be measured in numbers.
• It answers questions like "What kind?" or "Which type?".
EXAMPLES:
favorite colors of students (e.g., red, blue)
types of pets (e.g., dog, cat, bird)
levels of satisfaction (e.g., satisfied, neutral, dissatisfied).
Quantitative Data
• Quantitative data represents quantities or amounts and
can be measured or counted.
• It is always numerical and answers questions like "How
many?" or "How much?".
EXAMPLES:
height of students in centimeters
number of books on a shelf
temperature in degrees Celsius
Exercise A
For each scenario or statement below, identify whether the
data provided is qualitative (L) or quantitative (N).
L 1. Identifying the color of each car in the parking lot
N 2. Determining the number of students in each class
L 3. Rating a movie as “excellent”, “good”, or “poor”
N 4. Recording the grades of students in a mathematics exam
L 5. Describing the taste of different ice cream flavors
N 6. Counting the total pages in a book
L 7. Categorizing books based on their genres
N 8. Recording the time it takes to complete a race
L 9. Identifying the types of animals in a zoo
N 10. Noting the sizes of shoes in a store
Subtypes of
Data
Nominal
Labels or names
with no specific
order
Ordinal
Categories with an
order, but no exact
difference
Discrete
Whole numbers
you can count
Qualitative Data
Quantitative Data
Continuous Measured values
with decimals
Qualitative Data
Nominal
Categorical data with no specific order or ranking. It is
used to label or classify without implying any hierarchy.
EXAMPLES:
colors (red, blue, green)
types of fruits (apple, orange, banana)
favorite sports (basketball, soccer)
Qualitative Data
Ordinal
Categorical data with a meaningful order or ranking, but
the differences between categories are not measurable.
EXAMPLES:
Customer satisfaction levels
(satisfied, neutral, dissatisfied)
class rankings (first, second, third)
sizes of clothing (small, medium, large)
Quantitative Data
Discrete
Quantitative data that consists of countable, distinct
values. It often involves whole numbers.
EXAMPLES:
number of students in a class
number of questions in an exam
number of goals scored in a game
Quantitative Data
Continuous
Quantitative data that can take any value within a range,
often involving measurements. It includes fractions or
decimals.
EXAMPLES:
height of students (e.g., 160.5 cm)
weight (e.g., 55.2 kg)
temperature (e.g., 36.7°C)
Exercise B
For each scenario or statement below, identify
whether the data provided is nominal (N),
ordinal (O), discrete (D), or continuous (C).
N 1. The blood types of students in the class (A, B, AB, O)
O 2. The finishing positions of athletes in a race (1st, 2nd, 3rd)
D 3. The number of books borrowed from the library last month
C 4. The heights of students measured in centimeters
N 5. The brands of smartphones used by students
O 6. The ratings of a movie (1 star, 2 stars, 3 stars, etc.)
D 7. The number of female students in the classroom
C 8. The distance(km) students travel from home to school
N 9. The types of weather observed during a week
C 10. The time it takes for students to complete a math test
Up Next
Methods of Data Collection
Thank You
for
Listening