Applied Managerial Decision-Making: Alternative and Null Hypothesis to Senior Managers at Widge Corp

The purpose of this memorandum is to give some insight on alternative and null hypothesis to senior managers at Widge Corp. and how these two things relate to our use of snack foods and the accumulation sales by doing so. We will also be discussing certain problems that may come about via other departments within the company and how we may use alternative and null hypothesis should we run into problems. With that being said, a formulation of a null hypothesis example will be given and an alternative hypothesis will be tested to counter this as well. The first thing to discuss is to give a brief description of the two in depth.

There are a number of basic steps that need to be done to come up with or develop a hypothesis in order to provide questions answering as well. First, you need to address a problem area and make statements regarding this problem area. Then you need to develop the hypothesis or its implications. Next, there comes deductive reasoning where you do the observing, testing, and experimenting regarding this subject area you are looking into. Once this is done, all of the research and data that has been gotten will be collected and analyzed where the results will either confirm or reject the hypothesis that you have given. A hypothesis is in fact just an explanation that is tentatively given which looks to verify a set of facts which will be tested by doing an ongoing investigative research. In fact qualitative and quantitative research are just two of the many ways in which you may develop this hypothesis where you address statements that express a relationship between two or more variables that are measured and that can make sure the implications for this testing of the variable relationships are very clear.

Null hypothesis is basically a hypothesis about the parameters of a given population. Its main purpose is to use experimental data to test the rightness of a null hypothesis. In doing this type of thing, you will hopefully be able to either prove that something is either right or wrong or to say it another way, the viable possibility will either be received or rejected. The null hypothesis is actually just the exact opposite of whatever it is that the person doing research thinks about a given subject area. It is a statement where there is no actual relationship between variables. (Ho or Hn). What Ho says is that there is no difference between a given whatever subject area is being researched and the Ho says that whatever was predicted was just the total opposite of what Ho said in the first place. The conclusion to this would be the final determination that the researcher would either keep or reject what was thought in favor of an alternative hypothesis which I will further elaborate on later. Even though the (Ho) hypothesis was not rejected or turned down, it still doesn't mean that it was not true. This could be for the simple fact that there was not enough evidence that was gathered to support the assumption that went against the Ho. To further expound on a null hypothesis, a rejection could basically not even produce the same result that was initially gotten in the beginning of the research or could even lead to changes that aren't even wanted per se.

Alternative hypothesis plain and simply put, is just the outcome of a statement that is suggested by a researcher and what he or she expects. The symbol for this would be something like (H1or HA) which would come about when a null hypothesis is rejected and it is a researchers' sound conclusion. This will come from the researchers prior studies of literature they have gotten to support their assumptions. Two types of alternative hypothesis are non-directional and directional hypothesis. The non-directional hypothesis is one that has no definite direction of the expected findings that are gotten. With that being said, a researcher may or may not be able to know what prediction to make from that of his or her past literature that was gotten. And the directional hypothesis is one that gives a direction of the expected findings by examining the relationships between variables other than by the comparing of groups. A good way to put it regarding null and alternative hypothesis is that whatever subject area is being studied, either something happened (which is the alternative hypothesis) or nothing at all happened (which is the null hypothesis). In fact, a hypothesis can only be either supported or not supported, it can't be proved or unproved. With all of this being said, an alternative hypothesis might be supported if the truth is not known which could lead to a change if the norm or status quo is gotten or achieved (Sharma, M. and Battina, S., 2009).

If we were to talk about the advantages and disadvantages of hypothesis testing we could say that an advantage would be that of parametric statistics involves testing or estimating the value of certain parameters such as a population means or its proportions. Now being that we talked about parametric statistics, we must also say that there is also that of nonparametric statistics which is basically based on data that is ranked (Dallal, G., 2008).

An example of an alternative hypothesis is something such as: wanting to know if children with a high IQ would exhibit more anxiety than those with a low IQ. And an example of a null hypothesis to this would be something such as: that there is not a significant difference in the anxiety level of children of High IQ's and those with low IQ's.

Advantage of parametric statistical hypothesis testing:

• · It indexes individual distributions within a particular family.

Advantage of nonparametric statistical hypothesis testing:

• · Makes less stringent demands of data
• · Can sometimes be used to get a quick answer with just a small bit of calculation

Disadvantage of nonparametric statistical hypothesis testing:

• · There are no parameters to describe and it becomes more difficult to make quantitative statements about the actual difference between populations.
• · It throws away information and never can detect if there are any differences when parametric tests are used.

In terms of Widge Corp, we could ensure that since people are so satisfied with our super pretzels, we could do research to see what other additions we could add to it in order to make it even more liked by our customers. Since other company's already are selling what they call super pretzels, it would be advantageous for us to go the extra edge to make ours more liked by the perspective market that are already buying them for their taste. We can basically see that there will be a need to use different types of methods in order to come up with the data that we need. This will inevitably make the leaders be able to have a better grasp and knowledge of how the customers are receiving our brand. As far as for marketing our main products and other products, there is also a need to have statistical testing done because this will not only reach our target market, but other groups as well. The importance of this is that so that we can look at the company data by using different types of formulas depending on what areas (i.e. geographically) we are trying to reach. This will also basically give us a synopsis whether or not our consumers will delve to choose one of our competitors over us when they are searching for the perfect snack food.

References:

Dallal, G., (2008). Nonparametric Statistics. Retrieved on January 23, 2012 from http://www.jerrydallal.com/LHSP/npar.htm

Null Hypothesis, (2007). What is a Null Hypothesis. Retrieved on January 24, 2012 from http://www.null-hypothesis.co.uk/science//item/what_is_a_null_hypothesis

Sharma, M. and Battina, S., (2009). Developing Hypothesis and Questions. Retrieved on January 23, 2012 from http://www.public.asu.edu/~kroel/www500/HYPOTHESIS