This document discusses different types of statistics and variables. Descriptive statistics organizes and presents data through graphical or textual means, while inferential statistics makes predictions about future events based on existing data. Variables can be independent, influencing other variables, or dependent, being influenced by others. Data can be measured on nominal, ordinal, interval, or ratio scales. Samples are subsets of populations used to collect numeric and non-numeric data, which can be continuous or discrete variables. Data is collected through surveys, existing records, experiments, or observations. Random sampling gives all population members an equal chance of selection, while non-random sampling uses methods like volunteers or convenience.

1. Statistics
Fundamentals and Applications

2. Classifications
DESCRIPTIVE STATISTICS
it is the process of organizing data effectively
with the aid of graphical or textual
presentation

3. Classification
INFERENTIAL STATISTICS
Statistics concerned about making intelligent
guesses about future events based on existing
data
- Concerned with obtaining information about
the characteristics of a population based on
some sample

7. Population – the collection of all elements of
interest being studied
Sample – a subset of a population

8. Data – facts that are collected, organized and
analyzed.
Variable – Characteristic of the subject being
studied. Examples: height, weight, name,
sales, student number, etc.

9. What are the variables presented in the
table?

10. Classification of Variables
Independent Variable – characteristics that
influences an outcome, or influences the
outcome of another variable.
Dependent variable – a characteristic which is
affected or influenced by another
characteristic

11. What is the dependent variable?
What are the independent variables?

12. Scales of Measurement
• Nominal Scale – characteristics that serve as
LABELS for identification

13. Scales of Measurement
Ordinal Scale – characteristics that has the
function of a nominal data but such
characteristics can be ranked

15. Scales of Measurement
Interval Scale –
measurements that maintain the characteristics
of an ordinal data
Intervals of observation can be expressed in
terms of a fixed measure
Arithmetic operations can be applied to such
measurements

16. Scales of Measurement
Ratio scale – measurements that have the
following characteristics
They can be ranked
Ratio between two observed values yield a
meaningful information
A Zero measurement means NONE

17. Scales of Measurement

18. Classification of Data/Variable
Numeric and Non-numeric data (Quantitative
and non quantitative data)
Continuous Variables and Discrete Variables

19. Data Collection (How are data
collected)
Surveys (sample surveys)
Existing collection of data (obtain data from data
which are already collected)
Experimental studies (conduct experiments)
Observational studies ( Observe the subject
without influencing them)

20. Sampling Techniques
Random Sampling – a sampling where every
member of the population has an equal
chance of being included in the sample.
- Drawing lots
- Table of random numbers
- Systematic sampling
- Stratified random sampling

21. Sampling Techniques
Non-Random Sampling
Volunteer sampling
Judgement sampling (targeted sampling)
Convenience sampling