Business Decision Making - Essay Example

Running Head: BUSINESS DECISION MAKING Business Decision Making in APA Style by Decision making is very important in business organization since this identifies the most strategic direction that it can take considering its internal and external environments. Hypothesis testing is a statistical tool which aids managers and other decision makers in coming up and choosing among the various alternatives. Hypothesis testing is defined as "the process of choosing between competing hypotheses about a probability distribution, based on observed data from the distribution" (Hypothesis Testing).

As the name implies, the test utilizes hypotheses in order to come up with a decision. Statistically speaking, there are two types of hypothesis namely, the null and the alternative hypotheses. During a statistical test, the null hypothesis is tested against the alternative hypothesis. It should be noted that "null" means nothing and that null hypothesis means that nothing is present (Hyperstat Online 2008). Statistical tests are conducted in order to test the viability of the null hypothesis.

On the other hand, the alternative hypothesis is an alternative hypothesis which can be assumed if the null hypothesis is rejected. In the case of snack foods, hypothesis testing can be used in order to make business decisions. For example, the company is deciding whether to launch a healthier brand of corn chips to target weight watchers. After an intensive and extensive data gathering, the company wants to test if the introduction will have an impact in their current market share of 35%. Thus, they will need to conduct either one or two tailed test.

A one-tailed test looks for an increase or decrease in the parameter under consideration while a two-tailed test looks for any change in the parameter. We will illustrate this further by applying the five steps in hypothesis testing. The first step in hypothesis testing is stating the null hypothesis. For both one and two tailed test, the null hypothesis that the market share will remain 35% can be stated as Ho: x = 36%. Next step is to state the alternative hypothesis. Since one-tailed test is concerned on increase or decrease of the market share, the Ha or alternative hypothesis can be stated as Ha: x > 36% if the company expects to gain more sales through the brand introduction.

In two-tailed test however, the alternative hypothesis can go in either direction. Thus, market share can increase or decrease. The alternative hypothesis is then stated as Ha: x 36%. The next step is specifying a certain level of significance which the null hypothesis will be tested. The test statistic and the corresponding p value will then be calculated. It should be noted that before a hypothesis test is made, assumptions regarding t and z tests must be understood. Both of these tests assume that the variables are generated from a normally distributed data set.

However, the z-test assumes that the standard deviation is known while the t-test assumes that it is unknown (Walpole et. al, 2001). After which, a conclusion of whether the null hypothesis is rejected or accepted is made. The acceptance of the null hypothesis is not a proof that what it states is true. It simply is an indication that under the specific conditions there are no solid grounds to doubt its truthfulness. Type I risk is the chance of rejecting the null hypothesis when it is true (Walpole 2001).

On the other hand, the alternative hypothesis is considered to be more acceptable if the null hypothesis is rejected. Type II risk is the chance of accepting the alternative hypothesis when it is false (Walpole 2001). ReferencesHypothesis Testing. (n. d). Retrieved 14 March 2008, from www.math.uah.edu/stat/hypothesis/index.xhtml Hyperstat Online. (2008). Retrieved 14 March 2008, from http://davidmlane.com/hyperstat/Walpole, R., et. al. (2001). Probability and Statistics for Engineers and Scientists.

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