+ All Categories
Home > Documents > RESEARCH METHODS SEMINAR CLASS SESSION 1. The requirement of embarking a research – You need a...

RESEARCH METHODS SEMINAR CLASS SESSION 1. The requirement of embarking a research – You need a...

Date post: 17-Dec-2015
Category:
Upload: stewart-moore
View: 213 times
Download: 0 times
Share this document with a friend
22
RESEARCH METHODS SEMINAR CLASS SESSION 1
Transcript

RESEARCH METHODS

SEMINAR CLASSSESSION 1

• The requirement of embarking a research

– You need a title.

– You need to submit a proposal (20%). – Filled up -The proposal form

– You need to wait until your proposal is approved.

1. Problem identification…………………….Chap 12. Formulate research questions………….Chap 13. Literature review ……………………………..chap 24. Methodology - Research philosophy and

approach…………………………………………..Chap 35. Research design…………………………………Chap 36. Data collection……………………………………Chap 47. Data processing & analysis………………….Chap 48. Conclusion & reports…………………………..Chap 5

Research Process

• The Research Problem

– What is a research problem

– How to write a research problem statement

Literature ReviewWhat is Literature Review ?◦ Highlight what has been done so far, such as

Approaches Methods used Variables used Statistical procedures

Why it is important? To Improve research methodology Focus on research problem

Deeper understanding subject matter Cater to knowledge base for research area

Gain wider knowledge Contextualize research findings

Contribution Ensure novelty in work Avoid reinventing the wheel

How to write a Literature Review Block method

Class Exercise

30 MINUTES

Create a research title

Define the research problem

Develop the research questions

SESSION 2

Methodology

• How you want to conduct your research

• Type of approach– Quantitative– Qualitative

• Different approach – different methodology used

• How well does the sample represent the population?

Population SampleParameters Statistics

Sample Representative

( , ) ( , )X s

Estimation

• Determination of a suitable sample size– Base on the theory of probability • The larger the sample size, the lower the chances of

error in generalizing.

– The determination of sample size influenced by,• Confidence level of data, level of certainty that the

characteristics of the data collected will represent the characteritics of the total population.• Margin of error tolerated, level of accuracy required for

any estimates made from the sample• Type of analysis undertaken.• Size of population from which the sample is to be

drawn

Primary Data Collection

Two Basic Sampling Methodologies

Probability Samples

Simple RandomSampling

SystematicSampling

ClusterSampling

StratifiedSampling

Nonprobability Samples

ConvenienceSampling

ReferralSampling

JudgmentSampling

QuotaSampling

Probability: Each member of the population has an equal and known probability of being included in the sampleNonprobability: The probability of selecting members of the population is unknown/unequal.

Measurement & Scales• Variables– A logical grouping – Construct or property to be studied

• Type of variables – DV– IV– Moderating V– Extraneous V– Intervening V

Measurement & Scales

• There are four levels of measurement available to the researcher:

1. Nominal

2. Ordinal

3. Interval

4. Ratio

• Measurement is achieved through the use of scales. A scale is a measurement tool that can be used to measure a question with a predetermined number

Data Collection

Secondary Data- Internal - External

Primary Data

ObservationHumanElectronicMechanical

Quantitative

Self-Completion SurveysRegular mailOvernight deliveryFaxInternetDrop off/pick up

Interviewer-Completed SurveysTelephoneShopping MallHome, Office, etc.Observation

InterviewsDepth InterviewsFocus GroupsCase StudiesProjective Techniques

Qualitative

ObservationHumanElectronic

Questionnaire Development

Classification questions

Extract from a survey codebook

Class Exercise

Develop a Simple Questionnaires

20 MINUTES

• Descriptive Statistics– Measure of location– Mean– Median– Mode– Measure of spread– Variance– Standard deviation– Measure of shapes

Analysis of Data

Hypothesis Testing

• Hypothesis testing: a statistical procedure used to “accept” or “reject” the hypothesis based on sample information

• Intuitive hypothesis testing: when someone uses something he or she has observed to see if it agrees with or refutes his or her belief about that topic…so we use hypothesis testing in our lives all the time

• Example of Hypothesis• Product quality has the significant influence

on customer loyalty• Brand name has the significant influence on

customer loyalty

• Inference : the reasoning involved in drawing a conclusion or making a logical judgment on the basis of circumstantial evidence and prior conclusions rather than on the basis of direct observation.

• Standard Deviation• T-Test – test of significant differences between 2 mean,

• Independent• Dependents

• ANOVA (One way analysis of variance)• Correlation coefficient

Inferential Statistics

Class Exercise

Preparing your research proposal

30 MINUTES


Recommended