Business Research Methodology<br />Business research methods vary depending on the size of the company and the type of information needed.<br />For instance, customer research may involve finding out both a customer’s feelings about and experiences using a product or service.<br />The methods used to gauge customer satisfaction may be questionnaires, interviews or seminars.<br />Researching public data can provide businesses with statistics on financial and educational information<br />Business research used for advertising purposes<br />
Business Research Process<br />Problem definition and research proposal<br />Selecting Which Business Method to Use<br />How to Select From Among Public Data Collection Tools<br />Methodology:- Appreciative Inquiry- Case Study Design- Focus Groups- Interview Design- Listening- Questioning (face to face)- Questionnaires- Surveys<br />Analyzing, Interpreting and Reporting Results<br />
Sampling Techniques<br />Sampling a subset of individual observations within a population of individuals intended to yield some knowledge about the population of concernVarious types of Sampling Techniques:<br />Simple Random Sampling: In a simple random sample ('SRS') of a given size, all such subsets of the frame are given an equal probability.<br />Systematic Sampling: Relies on arranging the target population according to some ordering scheme<br />Stratified Sampling: Where the population embraces a number of distinct categories, the frame can be organized by these categories into separate "strata."<br />Each stratum is then sampled as an independent sub-population, out of which individual elements can be randomly selected<br />
Multivariate Analysis Methods<br />Two general types of MVA technique<br />Analysis of dependence<br />- Where one (or more) variables are dependent variables, to be explained or predicted by others<br />- E.g. Multiple regression, PLS, MDA<br />Analysis of interdependence<br />- No variables thought of as “dependent”<br />- Look at the relationships among variables, objects or cases<br />- E.g. cluster analysis, factor analysis<br />
Correlation<br /><ul><li>For example, height and weight are related; taller people tend to be heavier than shorter people.
The relationship isn't perfect. People of the same height vary in weight, and you can easily think of two people you know where the shorter one is heavier than the taller one.
Nonetheless, the average weight of people 5'5'' is less than the average weight of people 5'6'', and their average weight is less than that of people 5'7'', etc.
Correlation can tell you just how much of the variation in peoples' weights is related to their heights.</li></li></ul><li>Testing Statistical Hypothesis<br />There are many different tests for the many different kinds of data.<br />A way to get started is to understand what kind of data you have. Are the variables quantitative or qualitative?<br />Certain tests are for certain types of data depending on the size, distribution or scale.<br />Also, it is important to understand how samples of data can differ.<br />The 3 primary characteristics of quantitative data are: central tendency, spread, and shape.<br />
T test for two means: In both the one- and two-tailed versions of the small two-sample t-test, we assume that the means of the two populations are equal. To use a t-test for small (independent) samples, the following conditions must be met:<br />The samples must be selected randomly.<br />The samples must be independent.<br />Each population must have a normal distribution.<br />A small two sample t-test is used to test the difference between two population means m1 and m2 when the sample size for at least one population is less than 30<br />One way Anova Test: The one-way ANOVA F-test is used to identify if there are differences between subject effects. For instance, to investigate the effect of a certain new drug on the number of white blood cells, in an experiment the drug is given to three different groups, one of healthy people, one with people with a light form of the considered disease and one with a severe form of the disease.<br />