# Journal

Submitted By zeazainal
Words 34573
Pages 139
RESEARCH TECHNIQUES CLASSIFICATION

Uni-bi variant techniques
• Uni-variant analysis
– Frequency Tables (qualitative) – Descriptive Statistics (quantitative) – Summary Tables

• Bi-variant analysis
– Contingency Tables – Correlation analysis – Variance analysis
Research Techniques II 2

Multivariant analysis techniques
DESCRIPTIVE TECHNIQUES Factor Analysis Correspondence Factor analysis Cluster Analysis Output Association / Reducing dimensions Typology EXPLANATORY TECHNIQUES Varian Analysis Regression Analysis Discriminant Analysis CHAID AID Conjoint Analysis Multidimensional Analysis
Research Techniques II

Output Experiment results Prediction / Classification

Segmentation Ideal Product Image / Positioning
3

VARIANCE ANALYSIS ONE FACTOR
A random design is that where random simples are selected for each treatment. Yij = µi + εij where Yij: it is the answer of observation j who has received the treatment i µi: it is the mean of the treatment i, and εij: it is a specific random part for each observation Hypotheses: H0 : µ1 = µ2 = . . . = µp Ha: At least two treatments have different means. Assumptions: 1. The probability distributions of the p populations follow a normal distribution. 2. The variances of the p populations are equal. 3. Samples are selected randomly and independently from the populations. This model could be also expressed as the following: Yij = µ + τi + εij Where µ: it is the general mean, and τi: it is the differential effect of the treatment i. H 0 : τ 1 = τ2 = . . . = τp Ha: At least two treatments have differential effect. The difference between one observation and the general mean is divided into an explained part (distance between the mean of the treatment and the general mean) and a residual part (distance between one observation and the mean of its treatment):
(Yij − Y ) = (Yij − Yi ) + (Yi − Y )

Research Techniques II

4

This

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