Statistics in Business - Paper Example

According to American Statistical Association (2001), Statistics is a branch of mathematics that deals with collection, analysis, interpretation and presentation of quantitative data. During the study of statistics, there are two types of data involved: qualitative and quantitative data. Quantitative data provides information regarding qualities; that is information that can be measured and put down regarding numbers (Kish, 2012). Quantitative data gives information about height, size, length and weight. On the other hand, qualitative data provide information related to quality; that is information thats hard to measure. For example, qualitative data gives information about color, shape, age and softness. Therefore, if we measure quantity, that is information about quantitative data, and while describing the quality, it is a statement of qualitative data.

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Qualitative and Quantitative Data and Research

Qualitative data are therefore used in qualitative research for the purpose of getting a clear understanding of the underlying opinions, reasons, and motivations. Qualitative data, therefore, is important in that it helps researchers to get insights of the problem for the purpose of developing ideas for potential qualitative study. A qualitative study can also be used to discover the trends in the opinions and thoughts. Qualitative data collection techniques differ using semi-structured or structured methods, and they may include: personal interviews, observations, and discussion groups (Kish, 2012). Quantitative data, on the other hand, is used to quantify the problem in research through the generation of data that can be interpreted into sensible statistics. It is therefore used to quantify behaviors, opinions as well as other defined variables and generalize the outcomes from a large population size. Thy type of data collection technique is less structured than quantitative data collection method (Francis, Robbins & Astley, 2014).

Evaluation of Charts and Tables used to Represent Qualitative and Quantitative Data

Charts, graphs, tables and other descriptive measures are important ways in which both qualitative and quantitative data can be presented. Therefore, it is important to know the different forms of data that one can present for the purpose of achieving adequate representation (American Statistical Association, 2001). The table bellows show the various methods in which both quantitative and qualitative data can be represented.

Table1: ways of representing qualitative and quantitative data

Levels of Data Measurement

There exist four different levels in which data can be measured: ordinal, nominal, interval or ratio. At times ratio and interval measurement levels are also referred to as scale or continuous. Researchers need to understand the different levels of measurement as these levels clearly, and the rephrasing of the research questions dictates the appropriateness and effectiveness of the statistical analysis. The nominal level of analysis is the first level. This level is where numbers in the variables are used for the purpose of classifying data only, and it is common with the use of letters, words and alpha-numeric symbols. The second; the level of measurement is the ordinal level. This measurement level involves the depiction of special ordered relationship between the observation data (Francis, Robbins & Astley, 2014). This measurement level is an indication of measurement ordering. The third level of measurement is known as the interval level. This level of measurement orders classifies and also specifies the distances between the intervals on the scale in a similar manner from low to high intervals. Finally, the fourth measurement level is the ration level. This level of measurement makes observations on top of having similar ranges. A zero value can as well be included in this level thus making this type of measurement to be different from other measurement levels (Kish, 2012). However, though all other properties are similar to interval level, ratio level differs in that the divisions between the scale points have equal distances separating them. It is, therefore, important for researchers to know that among all the levels, nominal measurement level is only used for the purpose of classifying data whereas the rest are more specific.

The Role of Statistics in Business Decision-Making

Statistical tools help in making a critical decisions such as personal concerns and issues in that it enables individuals to reduce the uncertainties that are linked with decision-making and that can affect the way of life. In addition, statistics minimizes guesswork regarding decision making (Kish, 2012). For instance, in a competitive market setting, businesses can succeed through making decisions that are based on instinct, approximations, and guesswork. Companies need to acquire scientific information and data and analyze them appropriately for the purpose of making profitable decisions for a particular business organization. An organization that is comfortable in primary areas of decision making has possibilities of succeeding, reduce risks exposure and minimize the chances of missing important opportunities (Francis, Robbins & Astley, 2014).

Business Research Questions or problems where statistics could be used

Statistics can be used to solve difficult business questions like calculating the rates of employee turnover. In this scenario, employers might want to reduce the rate of employee turnover and maximize on retention. Some possible questions would be: what is the rate of the current of employee turnover in the organization? How is the current employee turnover rates affecting the organization regarding cost? Most organizations do not know that high turnover rates could be costing them a lot. Based on the organizational objectives various sets of data such as vacancies, employee files and tenure of employees should be collected and examined to determine the underlying reasons behind high turnover rates within the organization.

References

Kish, L. (2012). Chance, Statistics, and Statisticians. Journal of the American Statistical Association, 73(361), 1. doi: 10.2307/2286508

Francis, L. J., Robbins, M., & Astley, J. (2014). Empirical theology in texts and tables: Qualitative, quantitative and comparative perspectives. Leiden: Brill.

American Statistical Association. (2001). The American Statistical Association: What is statistics? What do statisticians do? Author.