%0 Journal Article
%T The Effects of Parametric, Non-Parametric Tests and Processes in Inferential Statistics for Business Decision Making <br/>¡ªA Case of 7 Selected Small Business Enterprises in Uganda
%A Eldard Ssebbaale Mukasa
%A Wagima Christospher
%A Bakaki Ivan
%A Moses Kizito
%J Open Journal of Business and Management
%P 1510-1526
%@ 2329-3292
%D 2021
%I Scientific Research Publishing
%R 10.4236/ojbm.2021.93081
%X <span style=\"font-family:Verdana;\">The article gives a critique of parametric and nonparametric tests and
processes of</span><span><span style=\"font-family:Verdana;\"> inferential statistics in
forecasting customer </span><span style=\"font-family:Verdana;\">flows</span><span style=\"font-family:Verdana;\"> in 7 selected
small business enterprises in Uganda. Forecasting is one of the </span><span style=\"font-family:Verdana;\">decision making</span><span style=\"font-family:Verdana;\"> tools in a business enterprise.
Thi</span></span><span style=\"font-family:Verdana;\">s may include forecasting customer flows, volumes of sales </span><span style=\"font-family:Verdana;\">and</span><span style=\"font-family:Verdana;\"> many others. This is a vital component of </span><span style=\"font-family:Verdana;\">small</span> <span style=\"font-family:Verdana;\">businesses</span><span style=\"font-family:Verdana;\"> success. In the long run, what drives business success is the quality of
decisions and their implementation. Decisions based on a foundation of
knowledge and sound reasoning can lead the company into long-term prosperity;
conversely, decisions made </span><span style=\"font-family:Verdana;\">on the basis of</span><span style=\"font-family:Verdana;\"> flawed logic, emotionalism, or incomplete information can quickly put a
business out of commission. In many instances, business decisions have been
guided by parametric tests and processes and /or non-parametric tests and
processes of inferential statistics, which have subsequently affected the
futures of </span><span style=\"font-family:Verdana;\">business</span><span style=\"font-family:Verdana;\"> differently. As we
refer to </span><span style=\"font-family:Verdana;\">population</span><span style=\"font-family:Verdana;\"> mean knowledge for
hypothesis testing using parametric tests, we only refer to </span><span style=\"font-family:Verdana;\">mediums</span><span style=\"font-family:Verdana;\"> for samples, for nonparametric tests. A
parameter is a characteristic that describes a population. These may include ¦Ì
(the Mean), ¦Ä</span><sup><span style=\"font-family:Verdana;\">2</span></sup><span style=\"font-family:Verdana;\"> (the variance) of a distribution. We commonly refer
to the normal distribution, when it is symmetric, with the measures of central
tendency (Mean = medium = mode). </span><span style=\"font-family:Verdana;\">Usually</span><span style=\"font-family:Verdana;\"> these parameters are very </span><span style=\"font-family:Verdana;\">useful,</span><span style=\"font-family:Verdana;\">
%K Parametric Tests
%K Non-Parametric Tests
%K Business Decision Making
%K Small Enterprises
%K Statistical Inferences
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=109618