# LPS1 W1&2; Introduction to Statistical Analysis

```COLLEGE OF MARY IMMACULATE
JP Rizal St., Poblacion, Pandi, Bulacan
(044) 769.2021
https://www.collegeofmaryimmaculate.edu.ph
I. Introduction to Statistical Analysis.
A. Basic Statistical concepts and methods of statistical inference
1. Goal &amp; Steps in Statistical Analysis.
- involves collecting and scrutinizing every data sample in a set of items
from which samples can be drawn.
a. describe the nature of the data.
b. explore the relation of data to the population.
c. create a model to summarize.
d. prove the validity of the model.
e. employ predictive analytics to guide future actions.
2. Statistics is the mathematical method of dealing with the collecting,
presenting, analyzing, and utilizing of numerical facts and figures in order to
draw conclusion and aid in making decisions in uncertain world.
Historical background:
a. beginnings of recorded history.
b. registrations on land ownership
c. Used by gamblers in the games of chance
d. Political arrangement of the modern states
3. Branches of Statistics:
▪ Descriptive – seek only to describe and analyze data.
▪ Inferential – drawing conclusions or inferences from population that is
represented by a sample.
4. Types &amp; Sources of data
4.1 Data (informations)
▪ Qualitative or Categorical data – grouped into categories.
▪ Quantitative or Numerical data – based on quantity or numbers.
a. Discrete – measured at interval level but only as whole numbers.
b. Continuous – infinite possible values.
4.2 Sources of Data:
▪ Primary sources – from first hand or original data. Observation,
interview
▪ Secondary sources – from second hand data. Printed or electronic
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COLLEGE OF MARY IMMACULATE
JP Rizal St., Poblacion, Pandi, Bulacan
(044) 769.2021
https://www.collegeofmaryimmaculate.edu.ph
4.3 Population or universe is a complete set of all possible observations
or elements while a representative of a population is called a sample.
5. Levels of Measurement
a) Nominal – data consist of names, labels, or categories.
b) Ordinal – data that may be arranged in some order or sequence.
c) Interval – similar to ordinal but no absolute zero.
d) Ratio – the modification of the interval level, there is an absolute zero.
6. Sampling Techniques
6.1 Probability sampling “Chance process”
a. Random – everyone in the population was given an equal chance
to be selected as a member of the sample.
b. Stratified – Used for research work of population which is
composed of several categories called “strata”
c. Systematic – Used if the objects or individuals are arranged
alphabetically, numbering etc.
d. Cluster – sometimes called “area sampling” because of the
population spread out over a wide area.
6.2 Non-Probability sampling “Do not use the chance process”
a. Convenience – utilized results that are available.
b. Purposive – The object of the study has a unique characteristic
hence, not just anybody can be included as a sample for the study.
7. To determine the sample size from the population use the slovin’s formula.
𝑛=
𝑁
1+𝑁𝑒 2
where: n - sample size
e - margin of error
N- population size
References:
DeSmith.2018.Statistical Analysis Handbook. The Winchelsea Press, Drumlin Security Ltd,
Edinburgh.
McGraw Hill. 2019. Statistical Analysis with Software Application. McGrawHill Education.