Self assessment quantitative course



Self Assessment Quantitative Course

Self Assessment

After the completion of this course I have seen many changes as my skills and capabilities have enhanced. Because of critical analysis, my level of thinking as boosted up and it has positively effect on my decision making skills. Interpretation is one of the hardest things that need to be done properly in the test. I believe that I am little bit weak in the interpretation part. So, I have to pay a lot of attention towards this point in order to improve my skills.

This course has helped me out to select the topic that is related to the marketing field. So that, I can analyze the market conditions, demand of the product and customers needs and wants and the particular ways to identify and satisfy their needs.

Quantitative research is generally associated with the positivist/post positivist paradigm. It usually involves collecting and converting data into numerical form so that statistical calculations can be made and conclusions drawn. Objectivity is very important in quantitative research. Consequently, researchers take great care to avoid their own presence, behavior or attitude affecting the results (e.g. by changing the situation being studied or causing participants to behave differently). They also critically examine their methods and conclusions for any possible bias.

Multivariate Analysis 

In statistics, multivariate analysis is a technique involving two or more independent variables in relation to a dependent variable. In trying to determine the causes of variation in income, for example, researchers typically include a variety of independent variables such as educational attainment, occupation, race, gender, and family background (such as parents' education and occupation) (Theodore, 2003).

Multivariate analysis can be used to answer a number of different questions, among them (Hair, 1995): How accurately can we predict values on a dependent variable such as personal income using information about several independent variables? Which independent variable has the greatest effect on the dependent variable? How are the independent variables related to one another, and how does this affect each independent variable's effect on the dependent variable? How do the direct effects of independent variables on the dependent variable compare with their indirect effects?

Multivariate techniques have grown rapidly in sociological usage, especially in the United States and especially with the advent of computers capable of analyzing large datasets such as national surveys.

Multivariate analysis using projection techniques for latent variables has many advantages over the methods of regression traditional (Schafer, 1997):

can use information from multiple input variables, although these are not linearly independent

can work with matrices containing more variables than observations

Incomplete arrays can work, provided that the missing values ??are randomly distributed and do not exceed 10%

since they are based on the sequential extraction of the factors, which extract the greatest possible variability of the matrix X (explanatory variables, must be dependent) information can be separated from noise. X is assumed that the noise is measured.

Multivariate Techniques

The below mentioned are some of the techniques used in Multivariate Analysis (Theodore, 2003):

Principal Component Analysis

Factor Analysis

Discriminant Analysis

Canonical Correlation Analysis

Cluster Analysis

Dimensional Scaling Analysis

Structural Equation Model (SEM), causal ...