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Research is an organized inquiry carried out to provide information for solving problems.

It is the cornerstone of every science.

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“Statistics is the most important science in the whole world: for upon it depends the practical application of every other science and of every art: the one science essential to all political and social administration, all education, all organization based on experience, for it only gives results of our experience.”

- Florence Nightingale

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Research is finding answers to a question through the use of scientific methods.

Scientific methods is combining the powers of both deductive and inductive reasonings.

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Basic/Pure/Theoretical/Analytic Research and Applied/Empirical Research

Qualitative Research and Quantitative Research

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Basic Research

Inquiry on laws, theories, axioms, postulates, basic concepts in the field of inquiry.

Applied Research

Empirical investigation or inquiry using measurements or observations.

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Basic Research

The development of an estimation method of a linear model with General Error Distribution

Applied Research

Where are the CHED scholar-graduates? What is their profile?

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Qualitative Research

Inquiry that use information based on an understanding of the behavior of people and institutions, their values, rituals, symbols, beliefs, emotions.

Data collection requires complete participant observation , participant as observer, case study, focus group discussion.

Quantitative Research

Inquiry based on information collected through surveys, experiments, administrative records and which require statistical methods for analysis.

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Qualitative Research

A Case Study of a Lakeshore Family along Laguna de Bay.

Quantitative Research

Factors Influencing Employment Status of the Elderly in Thailand

Focus of this lecture is data analysis for quantitative applied research and the use of statistical methods of data analysis.

Focus groups and surveys have very different strengths

FOCUS GROUPS SURVEYSFocus groups excel at Surveys provide quantitativeproviding in-depth qualitative data that can be

generalizedinsights gleaned from a to larger populationssmall number of people

Surveys measure things –Focus groups do not frequencies of behavior,measure. They collect a differences in attitudes,breath of range of information intensity of feelings, etc.so that a “story” can be told.

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THE BEST INFORMATION CAN OFTEN BE GATHERED BY USING THE FOCUS GROUPS AND SURVEYS TOGETHER.

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Theory

From Nachmias and Nachmias and Babbie

Deductive phase

Inductive phase

Problem Hypothesis

Research Design

Measurement

Data Collection

Data Analysis

Generalization

Identification and Formulation of the Research Problem Determination of the Researchability of the Problem and

the Value of the Research Construction of the Research Objectives (Main Objective(s)

and Specific Objectives) Review of Literature and Interview of Experts to Get

Acquainted with the Research Problem Review and Finalization of the Research Objectives Construction of the Conceptual Framework of the Study

which includes the Assumptions of the Study Formulation of the Research Hypotheses Construction of the Operational Framework of the Study

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The more detailed procedure above is used for usual quantitative research in the social sciences and management sciences, in general, and business and economics.

Determination of Possible Research Obstacles

Construction of the Research Design - Sampling Design - Data Collection Method - Methods for Data Analysis(The above, along with a work plan and a

financial plan, constitute the research proposal)

Data Collection Data Processing Tabulation of Data Analysis and Interpretation of Data Drawing Conclusions and Making

Recommendations Reporting the Research Findings

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THESE ARE THE STEPS IN THE RESEARCH PROCESS WHERE STATISTICAL

METHODS ARE MOST USED

State who your subjects will be, how they will be selected, the conditions under which the data

will be collected, treatment variables to be

manipulated, what measuring instruments and data-

gathering techniques will be used, and how the data will be analyzed and

interpreted.

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Limitations- What are the limitations surrounding

your study and within which conclusions must be confined?

What limitations exist in your methods or approach-

sampling restrictions, uncontrolled variables, faulty instrumentation, and other compromises to internal and external validity?

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How have you arbitrarily narrowed the scope of the study?

Did you focus on selected aspects of the problem,

certain areas of interest, a limited range of subjects, and level of sophistication involved?

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Classifications of Statistical Methods* Descriptive Methods

* Inferential Methods

- estimation (point and interval) - Tests of

hypothesis

Choosing the Type of Analysis* Univariate* Multivariate

Question that needs to be answered

Type of Data

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Quantitative data or qualitative data (levels of measurement)

Cross section data or time series data Experimental , pseudo-experimental, or

non-experimental

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What factors can explain a certain characteristic of some entity(person, city, country, school)

Is a certain variable a function of a number of variables?

Are these characteristics correlated?

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Common Univariate Statistical

Methods

Used to answer the question involving the Statistical Models for independent observations on a dependent variable (usually survey data or experimental data for a single dependent variable)

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Dependent Variable

Independent Variables

Model

Quantitative All Quantitative Classical Regression

Quantitative Some QuantitativeSome QualitativeEmphasis on Quantitative

Classical Regression With Dummy Variables to Represent Qualitative Variables

Quantitative Some QuantitativeSome QualitativeEmphasis on Qualitative

Analysis of Covariance (ANOCOVA)

Quantitative All Qualitative Analysis of Variance (ANOVA)

Qualitative Some QuantitativeSome Qualitative

Logistic Regression(An Alternative is Discriminant Analysis, a Multivariate Statistical Method)

Qualitative All Qualitative Loglinear Models ( Chi-Square test of Independence is a special case)

Dependent Variable

Independent Variables

Model

Quantitative All Quantitative Classical RegressionRegression with Autocorrelated ErrorsCointegrated Data

Quantitative Some QuantitativeSome Qualitative

Classical Regression and Regression with Autocorrelated Errors With Dummy Variables to Represent Qualitative Variables

Qualitative Some QuantitativeSome Qualitative

Logistic Regression

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Some examples of describing data

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5

7

9

11

13

15

17

19

21

23

wholesaleprice

retail price

farm price

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Palay Prices, Quarter 1, 1999 – Quarter 4, 2004

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0

0.5

1

1.5

2

2.5

3

3.5

1970 1975 1980 1985 1990 1995 2000

Philippines Thai

Consists of a series of rectangular vertical bars where the length of the bar represents the magnitude demonstrated

each bar represents a time period or a class interval

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Poverty Trends in Indonesia

54.2

43.2

35

30

27.225.9

22.5

34.5

47.9

38.437.3

36.140.1

28.6

21.6

17.415.1

13.7

11.3

17.5

23.4

18.2 17.4 16.7

0

10

20

30

40

50

60

1976 1980 1984 1987 1990 1993 1996 1996* 1999 2002 2003 2004

Year

Po

vert

y I

nd

icat

or

Poor Population (in million)

Poverty Incidence(in %)

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0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00

Philippines Indonesia Thailand Korea, Rep.

4.10

7.98

8.84

9.90

2.36

1.87

1.58

1.20

GDP per capita Population

Consists of a series of horizontal rectangular bars whose lengths represent the magnitude to be demonstrated

each bar represents a category

Number of Beneficiary-Barangays

8

10

12

0 5 10 15

Quezon City

Mandaluyong

Makati

Lo

catio

n

Number of Barangays

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A circle which is divided into sectors in such a way that the area of each sector is proportional to the size of the quantity represented by the sector

Percentage distributionof main source of

Income

Wages

45%

others

18%

Entrepre

neurial

37%

30

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NCR ( 250, 000 and Above )

28%

24%11%

5%

6%

4%

22%

Food

Housing

Transport andCommunicationEducation

Fuel, Light, Water

HouseholdOperationOthers

* P250,000 and above annual income

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1980

1990

2000

1995

=10,000,0001980

1990

2000

1995

1980

1990

2000

1995

=10,000,000=10,000,000=10,000,000

The Population in the Philippines for the census years 1980 to 2000

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Poverty Mapping and Targeting Project

AGUSAN DEL NORTE

Measures of Central tendency Measures of Location Measures of Dispersion Measures of Skewness Measure of Kurtosis

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Summary Statistics

LIFE_EXP74

0

62.9167

64.7016

36.00a

11.8226

139.7738

-.439

.279

-1.096

.552

42.15

36.00

78.15

45.4164

76.4829

Valid

Missing

N

Mean

Median

Mode

Std. Deviation

Variance

Skewness

Std. Error of Skewness

Kurtosis

Std. Error of Kurtosis

Range

Minimum

Maximum

10

90

Percentiles

Multiple modes exist. The smallest value is showna.

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Consider the Data from NPC-Transco on energy sales in the Luzon grid.

The monthly database is from January 1985 to December 2002

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NPC Energy Sales in the Luzon Grid in the Philippines

January 1985-December 2002

0

500

1000

1500

2000

2500

3000

Jan-

85

Jan-

86

Jan-

87

Jan-

88

Jan-

89

Jan-

90

Jan-

91

Jan-

92

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

Jan-

01

Jan-

02

Month

En

erg

y S

ale

s(i

n 1

,00

0,0

00

kw

h)

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Trend- Sales is generally increasing except in January 2002 where a drop in level is noted.

Seasonality- There seems to be seasonality but there is volatility and disruptions in the pattern. These are evident in 1992 – 1994 and in 1999-2002.

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Unusual values- March 1993 and January 2002 seem to be much lower than their respective preceding data points.

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Tests concerning a population mean/proportion

Tests on the differences between population means/proportions from two independent populations

Tests on the differences between population means/proportions from two related populations

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Tests of relationshipsbetween two variables Y (variable ofinterest called dependent variable) and X used to study Y(referred to as independentvariable):1. ANOVA 2. SIMPLE LINEAR REGRESSION 3. CHI SQUARE TEST OF INDEPENDENCE

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1. ANOVA - Y is quantitative and X is qualitative and is called factor

2. SIMPLE LINEAR REGRESSION – Y is quantitative and X is quantitative

3. CHI SQUARE TEST OF INDEPENDENCE – Y and X are qualitative

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Ho : Y and X are not related Versus

Ha: Y and X are related

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Tests on the differences between population means/proportions from two or more independent populations

There are many ANOVA models. Among them are: one-factor ANOVA , two-factor ANOVA w/o replication ,

two-factor ANOVA w/ replications

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Ho:Beneficiaries from three locations have the same mean income

Ha: at least two mean incomes are different

or

Ho: uL=uV=uM

Ha: at least one inequality

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tests if there is linear relationship between two quantitative variables

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tests the presence of a relationship between two qualitative variables

Ho: variable A and variable B are not correlated

Ha:variable A and variable B are correlated

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Statistical Methods Computer Softwares : Editors like Microsoft Word Softwares like Excel for the Database, Graphs, Tables,

and Simple Analyses Statistical Softwares for Statistical Analysis – SPSS, SAS, STATA, MINITAB

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Construction of the Questionnaire Data Analysis: Descriptive Statistics Simple Inferential Statistics Classical Regression Analysis and

Logistic Regression Analysis ANOVA and ANOCOVA Chi-Square Test of Independence and

Simple Analyses of Categorical Data Factor Analysis and other Multivariate

Techniques

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◦ Asis, Maruja M.B. (2002). Formulating the Research Problem, reference material in the University of the Philippines Summer Workshops on Research Proposal Writing.

◦ Babbie, Earl (1992). The Practice of Social Research ( 6th ed.), California: Wadswoth Publishing Co.

◦ Bersales, Lisa Grace S.(2004). Research in Business and Economics, a lecture presented at the University of St. LA Salle, Bacolod City.

◦ Bersales, Lisa Grace S.(2003). Statistical Methods as Tools in Research and Development, a lecture presented at the U.P. Diliman College of Science Colloquia.

◦ Bersales, Lisa Grace S.(2003). The Importance of the Sampling Design in the Conduct of Research in the Social Sciences, a lecture presented at the U.P. Diliman College of Social Science and Philisophy.

◦ Bersales, Lisa Grace S., Dennis S. Mapa, and Genelyn Ma. F. Sarte (2003). Modules for Statistics of the Bangko Sentral ng Pilipinas Institute.

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◦ Borg, Walter R. Educational Research: An Introduction. David McKay Company, Inc. New York. 1963

◦ Meliton, Juanico B.(2002). Reviewing Related Literature, reference material in the University of the Philippines Summer Workshops on Research Proposal Writing.

◦ Mercado, Cesar M.B. (2002). Overview of the Research Process, reference material in the University of the Philippines Summer Workshops on Research Proposal Writing.

◦ Mercado, Cesar M.B. (2002). Proposal and Report Writing, reference material in the University of the Philippines Summer Workshops on Research Proposal Writing.

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◦ Nachmias, Chava F. and David Nachmias, 1996. Research Methods in the Social Sciences( 5th ed.), New York: St. Martin’s Press.

◦ Phillips, Estelle M. and Derek S. Pugh (2000). How to Get a Ph.D.: A Handbook for Students and Their Supervisors (3rd ed), Philadelphia: Open University Press.

◦ Statistical Research and Training Center (SRTC) Training Module on Research.

◦ University of the Philippines Statistical Center Research Foundation (UPSCRF) Module on Statistical Methods for the Social Sciences.

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Thank you very much for listening!

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Acknowledgement:

Lisa Grace S. Bersales, Ph.D.Dean and Professor of

StatisticsU.P. School of Statistics

Josefina V. AlmedaUndergraduate Director U.P. School of Statistics