The document provides an overview of data management and statistics, including methods of data gathering such as interviews, questionnaires, registrations, observations, and experiments. It discusses types of variables (qualitative, quantitative, discrete, continuous) and levels of measurement (nominal, ordinal, interval, ratio) with examples. It also highlights different forms for presenting data, including textual, tabular, and graphical formats like line, bar, pie graphs, and pictographs.

1. DATA MANAGEMENT

2. STATISTICS
• It is a branch of
Mathematics dealing with
the collection,
organization,
presentation, analysis and
interpretation of data.

3. STATISTICS
•A systematic collection
of data on
measurement.

4. DATA
GATHERING
• Direct or Interview
Method
• Indirect or Questionnaire
Method
• Registration Method
• Observation Method
• Experimental Method

5. Direct or
Interview Method
• Person to person
encounter between the
source of information,
the interviewee and the
one gathers
information, the
interviewer.
Personal Interview
Telephonic Interview

6. Indirect or
Questionnaire
Method
• Technique in which
questionnaire is used to
elicit the information or
data needed.
• The questionnaire is
consisting of questions
printed or type written
in the definite order on a
form or a set of forms.

7. Registration
Method
• Obtains data from the
records of the government
agency authorized by law
to keep such data or
information and made
these available to the
researchers.
Birth and Death Rates
Number of Registered Cars
List of Registered Voters

8. Observation
Method
• Technique in which data particularly
those pertaining to the behaviors of
individuals or group of individuals
during the given situation.
Example:
Allowing children to play with
selected toys to determine which is
most popular
Children’s Behavior
Costumer’s Movement
Number of costumers visiting to
the store
Costumers’ responses in a retail
store

9. Experimental
Method
• A system used to gather data from
the results of performed series of
experiments on some controlled
and experimental variables.
• Commonly used in scientific
inquiries
• Based on observation
Example:
Drinking alcohol negatively affects
memory
If students sleep less before the
exam, then their grades on the
exam will be lower

10. CLASSIFICATIO
N OF
VARIABLES
• Qualitative /
Categorical
Variable
• Quantitative
Variable

11. Qualitative /
Categorical Variable
• A variable that yields
categorical responses
Example:
Names
Color
Marital Status

12. Quantitative
Variable
• A variable that takes on
numerical values
representing the
amount or quantity.
Example:
Height
Weight
Number of Siblings

13. 2 TYPES OF QUANTITATIVE VARIABLE
DISCRETE CONTINUOUS
• A variable which can be
assume finite
• Usually measured by
counting or enumeration
Example:
 Number of students in a
class
 Number of eggs in a
basket
 Family members
• A variable which can be
assume infinitely many
corresponding to line
interval.
Example:
 Weight/Height
 Windspeed
 Time required to run a
mile

14. FOUR LEVELS OF MEASUREMENTS
NOMINAL
SCALE
1
ORDINAL
SCALE
2
INTERVAL
SCALE
3
RATIO SCALE
4

15. NOMINAL
• Assign names or labels to observation in purely arbitrary sequence
• Labels are used to classify the respondents or objects without
ordering
Examples:
Gender
Brand of Cellphones
Religion
Civil Status
Phone Number
Main Source of Allowance

16. ORDINAL
• Assign numbers or labels to observation with
implied ordering
• Ranking on respondents' preferences
Examples:
Stage of Cancer
T-Shirt Size
Educational Level
Satisfaction Level

17. INTERVAL
• Reflect distance between rank position of the respondents or
objects in equal units
• This scale gives the distance between any two numbers of
known sizes
• No true absolute zero point
• Can be manipulated algebraically by addition and subtraction
but not multiplication and division
Examples:
Temperature
SAT Scores

18. RATIO
• Reflect the existence of true absolute zero point as its origin
• Doesn’t have negative number unlike interval
• Ratio of two scale point is independent of the unit of
measurement
• Can be manipulated algebraically by multiplication and division
and has all properties of Interval data
Examples:
Distance
Height
Weight

19. TRY THIS
1. Hair color of women on a high school
tennis team
2. Temperatures of 22 selected refrigerators
3. Number of pages in your statistics book
4. The ratings of a movie ranging from poor
to good to excellent
5. Nationality

22. Different Ways or Forms to Present Data
• Textual Form – Makes use of words, sentences, and
paragraphs in presentation

23. Different Ways or Forms to Present Data
• Tabular Form – Systematic presentation of data in rows and
columns. Used when related numerical facts need to be classified
in arrays
Simple
Focus on the readers’ attention on the data rather than on the
form
Meanings and significance of information being presented are
clear

24. Different Ways or Forms to Present Data
• Graphical Form – Shows numerical values or relationship
in pictorial form. Makes use of graph, symbols or visual
aids
Accurate – Reflect the highest degree accuracy
Simple – Basic design should be simple and straight
forward
Clear – It should be easily read and understood
Attractive – Holding a neat, dignified and professional
appearance

25. TYPES OF
GRAPHS
Line Graph
1. Data cover a long period of time
2. Several series are compared
3. Movements are to be emphasized
4. Trends are to be established
5. Estimates are to be forcasted

26. TYPES OF
GRAPHS
Bar Graph
1. Numerical values of an item over a
period of time are compared
2. Consist of regular bars represents the
quantity of frequency for each
category

27. TYPES OF
GRAPHS
Pie Graph
1. Used to show the percentage or
composition by parts of a whole

28. TYPES OF
GRAPHS
Pictograph or Pictogram
1. Used to immediately suggest the
nature of data