28 Jun RESEARCH-SOCIOLOGY
MARKETING
NAME OF THE STUDENT
COURSE
TUTOR
INSTITUTION
DATE
Research
In the past old methods have been applied in the modeling of structural equation and in this case the analysis on covariance structure and the squares that are partial least. The third option has been introduced recently namely the component analysis that has been generally structured. It is easier to tabulate data through frequency distribution than operating on raw data. This is due to the simple algorithms presented by the table for calculation. For instance, the mean, median and standard deviation (Malhotra, 1996).
Testing of statistical hypothesis is built on evaluation on the differences as well as the similarities found in frequency distributions. The evaluation includes central tendency measures, averages, in addition to variability measures or else statistical dispersion for instance variance or standard deviation. Frequency distributions also come in letters. They are applied in analyses to break codes referring them to relative letter frequencies in diverse languages (Malhotra, 1996).
Cross tabulations or cross tabs or else contingency tables treat two variables, or more, simultaneously. However, since these variables appear in a table that is two-dimensional, cross tabbing variables that exceed two is not easy to visualize given that over two dimensions are required. Cross tabulation is performed for both ordinal and nominal variables. When carrying out data analysis within marketing research cross tabulation facilitates the best method. Cross tabulation breaks up the sample into subordinate groups with the aim of showing the contrast between dependent variables in various subgroups (Malhotra, 1996).
Interpreting samples with a t test is simple for it involves making a comparison of two samples with the use of their means. The output tells the difference of one mean gotten from a sample of one group with another mean from another group. It notifies of the statistical significance of the difference. Collecting data for t-tests is easy for its validity is not based on bulk; it merely needs a value from every subject. Data calculation can be done using a computer thus no statistical training is required.
Market segmentation involves identifying as well as targeting individual groups with similarities. Markets are segmented depending with the product and service needs. In addition by being sensitive to price depending with the geographical area, the demographic segments or else by lifestyles and psychographics. Factor analysis divides the respondents into sections on a basis of mutual exclusiveness. It produces consistent groups of respondent who possess similar attitudes as well as perceptions. This technique is crucial during the development of targeting, positioning along with marketing strategies (DecisionAnalyst, 2011).
Product decisions are made by first identifying estimated quantity that needs to be put on sale every year. This paves way for new products into the market but should be based on estimates done by the manager regarding the performance of the products. The tools that are used during this process of decision making through management are quantitative techniques and mathematical models (Urban & Lipstein, 1968).
A wholesaler finds it difficult to gauge the response by the consumer regarding price or promotion when the retailer uses a pricing scheme as well as a promotion scheme that is not suggested by the wholesaler. In addition the retailer could be unwilling to have a share of the data from the end-consumer, in the company of the wholesaler. It is thus important to leave the pricing decisions to the sales teams or else the bid-response teams. The selling price will be based on the transaction total value or chances of winning transaction bids (An & Fromm, 2005).
For there to be commitment in the relationships involved in distribution factors like reputation, communication level along with relationship history among the involved parties need to be put into consideration (Anderson & Weitz, 1992).
REFERENCES
An, C., & Fromm, H. (2005). Supply chain management on demand:strategies, technologies, applications. Oklahoma: Springer.
Anderson, E., & Weitz, B. (1992). The Use of Pledges to Build and Sustain Commitment in Distribution Channels. Journal of Marketing and Research , 29 (1), 18-34.
DecisionAnalyst. (2011). Marketing Segmentation. Retrieved July 29, 2011, from https://www.decisionanalyst.com/Services/MarketSegmentation.dai
Malhotra, N. K. (1996). Marketing research. New Jersey: Prentice Hall.
Urban, G. L., & Lipstein, B. (1968). A New Product Analysis and Decision Model. Management Science, , 14 (8), 490-519.
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