Scientific Skills and Processes

1. OBSERVING

Stating the properties or characteristics of an

object or event.

Kinds of Observation

• Physical Description

• Measuring or Counting

2. COMPARING

Recognizing similarities and differences in the

properties of objects and living things observed.

3. CLASSIFYING

Process of arranging, grouping or sorting things

according to some observable properties

they possess.

Can you group the following animals according

to their properties?

4. INFERRING

Logical mental process wherein one makes

explanations based on observations.

What can you say about the picture?

OBSERVING VS. INFERRING • The sky appears

red.• The sun is going

down the horizon.• There are four

people in the picture.• It is near dusk.

• The four people are in a resort island.

OBSERVING VS. INFERRING

5. PREDICTINGProcess of

estimating or forecasting a

future event or trend based on

previous experiences or

observation

Which figure should come next?

Process of predicting data or events within the graph of the given data

Process of predicting data or events beyond the scope of the given graph of the data

048121620242832

0 2 4 6 8 10 12 14 16

time (second)

dist

ance

(met

er)

What is the distance when the time is 4 seconds?

048121620242832

0 2 4 6 8 10 12 14 16

time (second)

dist

ance

(met

er)

What is the distance when the time is 12 seconds?

6. MEASURING

Process of quantifying

observations or properties of

objects

MEASUREMENTCOMPARING A QUANTITY TO

AN APPROPRIATE SCALE OR STANDARD

Closeness of a measured value to the true value

Degree of agreement between several values obtained under the same conditions

Neither accurate nor precise

Given 3 darts:

Precise but not accurate

Both accurate and precise

How is the accuracy and precision of measurements

determined?

• Given the following experimental data for the density of water:

Density (g/ml)

1 0.962 0.993 1.004 1.02

If the accepted value for the density of water is 1.00g/ml, which measurement is the most ACCURATE?

Density (g/ml)

1 0.962 0.993 1.004 1.02

Average: 0.99 g/ml

Get the average.

7. Formulating the Problem

• Be stated beginning with the words Why and How.

• Contain the subject of the research.• Indicate the variable/s being tested and

the corresponding responding variable/s• Give its readers an idea of what the

experiment is about.

8. Making a Hypothesis• An educated guess to a problem

Example:

What causes the spoilage of food?Why does the heartbeat of a person vary?

9. CONTROLLING VARIABLES

Factors that affect the behavior or properties of an object or event

Example:What conditions affect the

growth of plants?Amount of fertilizerType of soilAmount of waterAmount of sunlightKind of plant specie

These are all

VARIABLES !

KINDS OF VARIABLES

• MANIPULATED

• CONTROLLED

• RESPONDING

Example: How does the amount of fertilizer affect the growth of a

tomato plant?

Manipulated Variable

Responding Variable

Controlled Variable

10. ORGANIZING DATA• PRESENTATION OF THE DATA FOR ANALYSIS

Pictorial representation of data

Making a data table

• Make a data table• Identify the variables

• Foliage/leaves broom, roofing• Nuts/fruits food, drinks, husks• Roots disinfectant, medicine,

driftwood• Cellulose paper, plywood• Lumber toys, posts, fuel

A group of students made a survey of the products derived from coconut trees. They came up with the following data:

Products obtained from parts of the coconut tree

Part of the coconut tree

Product

Foliage/leaves broom, roofing

Nuts/fruits food, drinks, husks

Roots disinfectant, medicine, driftwood

Cellulose paper, plywood

Lumber toys, posts, fuel

Interpreting tables and graphs

Interpreting tablesNumber of marbles Levels of water

0 501 522 543 566 629 68

13 76

As the number of marbles increases, the level of water also

increases.

0

4

8

12

16

20

24

28

32

36

0 1 2 3 4 5 6 7 8 9

time (s)

velo

city

(m/s

)Interpreting graphs

11. DERIVING CONCLUSIONS

• A STATEMENT

OF THE ANSWER TO

THE PROBLEM OF THE

EXPERIMENT

Bread Type

Condition of Result

Moisture Sunlight

Temperature

AMoistene

dExpose

dNear the window

Plenty of

molds grew

B Dry No molds grew

Example: Given the following data table:

Bread Type

Condition of ResultMoisture Sunlight Temperatur

eA

MoistenedExposed Near the

window

Plenty of

molds grew

B Dry No molds grew

Identify the manipulated

variable.

Bread Type

Condition of Result

Moisture Sunlight

Temperature

AMoistene

dExpose

dNear the window

Plenty of

molds grew

B Dry No molds grew

Identify the responding

variable.

Bread Type

Condition of Result

Moisture Sunlight

Temperature

AMoistene

dExpose

dNear the window

Plenty of

molds grew

B Dry No molds grew

State the best problem for the experiment

How does moisture affect the appearance of molds in bread?

Bread Type

Condition of Result

Moisture Sunlight

Temperature

AMoistene

dExpose

dNear the window

Plenty of

molds grew

B Dry No molds grew

What is the conclusion of the experiment