Statistically Analyze for Valid Business Decision - Case Study Example

Statistics Name Institutional Affiliation Introduction This paper focuses on the hypothesis testing for purposes of providing sufficient statistical assistance in order to help Michael Jenkins in making decisions regarding location, promotion, and last but not the least pricing strategy. The client’s dream of an upscale restaurant that would feature drinks, deserts and finest entrees in a strategic atmosphere would require many hypothetical testing methods. This hypotheses method in this essay will include; samples t-tests, ANOVA, paired sample t-test, independents sample t-test, and Chi-test to make his business a success. From the information given, it is clear that he needs additional and fundamental information on whether a good market exists for the services he intends to render. Furthermore, critical information needs to be provided, for instance, the best promotion strategy of the restaurant in his town upon opening. The design of his restaurant, the best location and the market price for the upscale entree are some of the many choices to be factored in. The company has promised that upon collection of reliable and valid information to patronizing the restaurant it create an accurate break analysis and compare it with the expected numbers of patrons. As a matter of fact, the research company had made several estimates of demand by employing a forecasting model. For instance, a 4% heads of household at the 12 post code locality claimed they were “very likely” to patronize it and if the same persons spent average of $200 a month in restaurants and would be willing $18 on average for an à la carte entrée. This model predicted an excellent performing restaurant in terms of its operation. The company had also obtained a demographic data on each and every post code within the metropolitan area. These were categorized into groups of four according to their similarities as summarized on appendix 1. The available demographic information shown suggests that either a locality within post codes 3,4, and 5 or among 6,7,8 and 9.The unfortunate scenario of these sets of post codes is that they are not close to each other and a comprehensive analysis shall be taken to assist Michael in this and other critical decisions. This report basically focuses on addressing ten identified questions and to conduct hypothesis and then statistically analyze this for sole purpose of assisting Michael in making informed and valid business decision that is based on verified evidence and finally to determine whether “Divine Elegance“ would be a success. Data Screening The very first step is data collection. Once this is collected and before it is analyzed is it of fundamental importance to view and screen this data. Based on the screening process, I believe that the data of 60 are logically inconsistent. The 60 data relating to the evening meal price, entrée customer is likely to pay 999 dollars. In reality this has a low possibility. In this regard, these data shall not be included in the data analysis. Consequently, I accept the null hypothesis. This then makes me to conclude that the price on average for the evening meal entrée is not significantly different from the 18 dollars. Ho: μ=18 H1: μ≠ 18 One-sample statistics What would you expect an average evening meal entree |340 |$18.8353 |$9.82784 |$.53299 | Probable Patron of the new restaurant? | Mean | N | Std. Deviation | Yes | $30.2364 | 110 | $8.81817 | No | $13.3826 | 230 | $3.69724 | Total | $18.8353 | 340 | $9.82784 | From the above it is evident that the majority of respondents who are likely patrons to Michaels restaurant are ready to pay $21-$30 with the largest group are ready to pay between $31 -$40 for their entrees. H1: μ ≠ $18 Therefore, the nulls hypothesis rejected. The mean of the sample is not $18. In layman’s words, the results are significant statistically and conclusions obtained from the test data in order to make inferences concerning the general population. In this particular case, we tested on whether potential patrons are ready to pay the $18.00 for an entrée as it was used as an assumed price for an entrée in the preliminary analysis. First, in the group of potential patrons tested it was found out that the average or mean price they were prepared to pay for an entrée was a sum of $30.23. It was also worth noting that over the larger sampled population the mean price people were ready to pay $18.83. This amount is slightly higher than the allowed price but it was also noted that the average for those unlikely to be patrons was over 13 dollars. Therefore, from this we are able to determine that patrons are mostly likely prepared to pay slightly more than the 18 dollars used in the forecasting. They are on average prepared to pay 30.23 dollars for an individual entrée. Variable 1 Variable 2 Mean 18.83529 18 Variance 96.58636 0 Observations 340 340 Pooled Variance 48.29318 Hypothesized Average Differencev 0 Df 678 t Stat 1.567188 P(T Read More