# DISCRIMINANT ANALYSIS

DISCRIMINANT ANALYSIS Introduction Discriminant Analysis undertakes the same task as multiple linear regressions with metric data. But in many cases we have to use categorical variables, such as loyality and disloyality, users and non users, buyers and non buyers of a product etc. Discriminant analysis is successfully used in these cases to find out the Read more about DISCRIMINANT ANALYSIS[…]

# MULTIDIMENSIONAL SCALING TECHNIQUE

MULTIDIMENSIONAL SCALING TECHNIQUE Introduction Multidimensional scaling is a powerful statistical technique used for representing the preferences of respondents into the groups of ‘Dimensions and Map’. MDS is useful in measuring the perception and distinctive images of the stimuli used in research. Perceived relationships among stimuli are then represented by means of a visual display using Read more about MULTIDIMENSIONAL SCALING TECHNIQUE[…]

# CONJOINT ANALYSIS

CONJOINT ANALYSIS Introduction Many time consumers seem to be confused in determining the relative importance of the attributes used in describing the features of the product or services. In such cases Conjoint analysis is used to measure the perceived values of specific product features on the basis of selected attributes. Conjoint analysis is a multivariate Read more about CONJOINT ANALYSIS[…]

# CLUSTER ANALYSIS

CLUSTER ANALYSIS Introduction Cluster analysis is a technique used to classify cases into groups that are relatively homogeneous within themselves and heterogeneous between each other, on the basis of certain characteristics. These groups are called clusters. It is not necessary that the clusters should comprise of people only, there could be clusters of brands, products Read more about CLUSTER ANALYSIS[…]

# FACTOR ANALYSIS

FACTOR ANALYSIS Introduction Factor analysis is used when the research problem involves a large number of variables making the analysis and interpretation of the problem difficult. The factor analysis helps the researcher to reduce a number of variables to be analyzed, thereby making the analysis easier. In factor analysis certain variables are combined into specific Read more about FACTOR ANALYSIS[…]

# MULTIPLE REGRESSION ANALYSIS

MULTIPLE REGRESSION ANALYSIS Introduction Multiple Regression analysis attempts to study the relationship between a dependent variable and a set of independent variables (one or more). It is a statistical technique that allows us to predict someone’s score on one variable on the basis of their scores on several other variables. When using multiple regression the Read more about MULTIPLE REGRESSION ANALYSIS[…]

# WILCOXON SIGNED RANK TEST FOR PAIRED SAMPLE

WILCOXON SIGNED RANK TEST FOR PAIRED SAMPLE Introduction Mann Whitney U test assumes the samples to be independent of each other. But, the condition may not hold in reality; as in many cases the sample observations seem to be related pair wise. Wilcoxon signed rank test is used to test the equality of population means Read more about WILCOXON SIGNED RANK TEST FOR PAIRED SAMPLE[…]

# FRIEDMAN’S TEST

FRIEDMAN’S TEST INTRODUCTION Friedman’s Test is an extension of the Wilcoxon test. Wilcoxon test can be applied to repeated-measures data if participants are assessed on two occasions or matched in pairs. In contrast, Friedman’s Test allows the analysis for the same sample of data assessed on two or more occasions or conditions or matched-subjects. It Read more about FRIEDMAN’S TEST[…]

# TWO- SAMPLE SIGN TEST

TWO- SAMPLE SIGN TEST CASE ANALYSIS- 1 PROBLEM The following data represents the amount of money spent per month by 15 housewives in Foreign Brand cosmetic items and Indian Brand cosmetic items. Table-1: Sample Data The hypotheses for the analysis are: Null hypothesis-H0: The average amount spent on Foreign Brand cosmetic items and Indian Brand Read more about TWO- SAMPLE SIGN TEST[…]