This is a practical inquiry by a business organization undertakes in order to obtain certain data, and analyze and interpret it towards better management of the business. Most companies use business researches in order to identify new areas to implement change, identify new markets and opportunities, and identify challenges and other areas that require decision making. For instance, a company may study the product market so as to identify new opportunities and threats so as to take a step that can put it in a safer situation (Bryman & Bell, 2007).
Business research and decision support and business intelligence systems
A decision support system is a computerized system based on a highly interactive software to help managers or decision-makers in organizations to reach quality and logical decisions. On the other hand, business intelligence is a set of computer tools that work together to transform unprocessed and raw data into useful information that can be used to analyze various issues regarding a business (Laudon & Laudon, 2000). Business research differs with DSS and BIS since it involves a practical examination that does not necessarily require computer elements to produce results, whereas, the latter are computerized to work under special tools and software to produce results.
- Types of business research studies include;
- Business Forecasting – can be used to determine long term investments and operations
- Competitive Analysis – identify potential threats from competitors
Pricing Strategy – determine the best pricing options available for the business
- Positioning Research – to determine how well to position the products in the market
- Market Segmentation – to determine the market segments available for easy targeting
- Advertising research etc. – determines how well the company can promote its products through advertising (Bryman & Bell, 2007)
- Confidence intervals
A confidence interval simply means a particular range that depicts how precise a statistical measurement is. It is common term in inferential statistics to give a probabilistic measurement that a particular parameter will be a value between a set of two given values (Altman & Gardner, 2000).
- “We are 95% confident that an interval estimate contains μ,” therefore, means that there is a probability that an interval will be produced in the statistical measurement will give or include a true value of μ as the parameter. Simply, it means that if we had to collect all possible samples from a particular population to compute confidence intervals for every sample, a good number of the intervals will include a true figure of the parameter; hence, 95% confidence will be when 95% of the computed intervals include a true parameter.
- Effect of sample size on the likelihood that a confidence interval contains the mean for a symmetric distribution.
Normally when trying to increase the level of confidence, the confidence interval will be greater e.g. 95-99. There is need to increase the size of an interval for assurance that the given interval includes the mean or population parameter. To produce precise intervals then the best thing is to increase the sample size. Increased sample size will reduce the interval width to achieve precision hence the likelihood for the mean to have asymmetric distribution.
Effect of sample size on the likelihood that a confidence interval contains
A reduced sample size decreases the reliability or precision of the interval. As the sample is reduced, the width of the interval gets longer hence increasing the chance that the mean for skewed distribution.
Altman, D. G., & Gardner, M. J. (2000). Statistics with confidence: Confidence intervals and statistical guidelines. Great Britain: BMJ Books.
Bryman, A., & Bell, E. (2007). Business research methods. Oxford: Oxford University Press.
Laudon, K. C., & Laudon, J. P. (2000). Management information systems: Organization and technology in the networked enterprise. Upper Saddle River, NJ: Prentice-Hall.