Business Statistics
Statistics is the methodology developed by scientists and mathematicians for interpretation and drawing conclusions from collected data (Isotalo, 2012). The main activities involved in statistics are collecting, processing, analyzing, interpreting, and presenting of data. Everything under these fields or anything remotely related to the fields, and the planning preceding these activities all belong to the domain of activities. Statistics is very broad and is not applied to science and mathematics alone but vast fields including business.
Qualitative versus Quantitative Data
Data used in statistical research can either be qualitative data or quantitative data. These data differs in their uses, their methods of collection, their analysis, and the sample used in the research. Qualitative data is usually descriptive data and gathers information that is not numerical in nature. This data is useful in conducting researches as case studies, ethnographic studies and phenomenological studies. Collection of the data is typically done through interviews, observations, objects, or documents from field work. The sample used in the collection of the data is normally a small number of non-representative cases (Castellan, 2010). Analysis of qualitative data is difficult because it requires a precise description in its collection. The types of data analysis used to analyze qualitative data are inductive processes such as themes and codes.
Quantitative data is usually in numerical form and can be put into two categories; discrete and continuous. Discrete data is data that can only occupy a finite number of possible values. Continuous data are not restricted to any possible values but can assume any value over a given range. Quantitative data is usually collected using surveys, questionnaires, and tests in the form of numbers. The sample used in the collection of the data is randomly selected or proportionally picked to represent the actual population involved in a research (Castellan, 2010). Quantitative data is used in experimental, single subject, descriptive correlational, and comparative researches. The analysis used in qualitative data analysis is usually simple and involves statistical procedures and deductive processes.
Representation of Qualitative and Quantitative Data
Qualitative data can either be represented using a pie chart or horizontal or vertical bar graph. A pie chart is a circular shaped structure that is divided into shapes that are pie-shaped each representing a data category known as class. To get the angle for any category, we multiply the relative frequency by 360 degrees corresponding to a full circle (Isotalo, 2012). The relative frequency is found by dividing the frequency in the class that is the number of observations by in a particular class by the total number of frequencies.
Horizontal bar graphs display frequencies and classes on the horizontal and vertical axis respectively. The height of the vertical bar is equal to the frequency of each class. The vertical bar displays classes and frequencies on the vertical and horizontal axis respectively. The length of the horizontal bars represents the frequency of each class. The bars in a bar graph do not touch each other.
Quantitative data can also be represented using horizontal and vertical bar graphs or using a histogram. The main difference between histograms and bar graphs is that the bars of a histogram touch each other (Isotalo, 2012). Bar graphs are suited for illustrating discrete qualitative data with only a few possible values. Histograms are formed from grouped qualitative data and show display the frequencies or relative frequencies of each class interval. The class intervals are groups of equal length that cover the range between the minimum and maximum data values without overlapping.
Levels of Data Measurement
Before a statistical analysis is conducted, data needs to be measured. How the measurement is done depends on the type of data involved in the analysis. The measurement procedures are different for different types of data but that can be classified using a few basic categories.
Nominal scales do not have any ordering and the categories are simply named. As such, they are the lowest level of measurement. Ordinal scales arrange data in a certain order and allow for comparison of two different types of dependant data. Interval scales are numerical in nature and contains intervals having the same interpretation throughout. The main disadvantage with this scale is that it lacks a true zero point. Finally, there is the ratio scale measurement that is the most sophisticated scale. It is similar to the interval scale but has a zero position that indicates the absence of measured quantity.
Role of Statistics in Business Decision-Making
Statistics allows businesses to carry out research concerning various issues affecting the businesses. This allows business leaders to avoid taking uncorroborated business strategies. Statistics is also used to support the decisions taking by business leaders by providing hard evidence concerning the decision. Statistics points out the relationship between two or more variables in the business environment giving the business management more control over the variables. Statistics is also very important in ensuring quality by providing means of measuring the production processes allowing for selection of the best process to minimize variations.
Some of the business research questions where statistics have been used in the past include; how to turn potential customers into established customers, and how will changes in the design of a product affect the sales of the product.
References
Castellan, C. M. (2010). Quantitative and Qualitative Research: A View for Clarity. International Journal of Education, 2(2), 1–14.
Isotalo, J. (2012). Basics of statistics. Retrieved from http://www.mv.helsinki.fi/home/jmisotal/BoS.pdf
