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GSBS6002 Foundations Of Business Analysis

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GSBS6002 Foundations Of Business Analysis

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Course Code: GSBS6002
University: The University Of Newcastle

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Country: Australia

Questions

How much are potential patrons willing to pay for a meal? Is $15 a reasonable price? Is there a difference in the willingness to pay between males and females?
Can Gloria expect all patrons to spend an average of $200 a month on food?
Which zip code area(s) provide the best location for the café? Does the expected average monthly spend differ between potential patrons residing in different zip codes?
Does the likelihood to patronize the café differ between people with different income levels?
Can the average amount people spend on food each month be explained by the average price people are willing to pay for meals, age, and gender?

Answer:

Introduction
The following study aims to analyze some of the factors that should be considered before establishing a start-up company. Gloria Jones is motivated by her dream to have her own café one day.  However, starting up a company comes with a myriad of challenges either personal or financial (Stevenson & Jarillo, 2007).
Starting up a company is such a challenge. An individual who takes this path needs to be highly motivated, with the will to accept work days which involve long hours and should be resilient enough to bounce back from shortfalls which almost certainly occur (Davidson & Wiklund, 2007). Most people who are driven into such ventures need to keep in mind that they are starting a company from ground level and building it (Sharma & Chrisma, 2007). Regardless of the excitement of the risks versus the reward tradeoff, the startup ‘CEO’ needs to be proficient in all aspects of the operations of the company which includes product development, marketing, and finance.
The following study aims at tackling some of the issues and factors which Gloria Jones needs to consider before setting up own café. Though she has a substantial capital from her savings from her restaurant supply she is curious to get informed. To make the inform Gloria Jones about the decisions she needs to make, the following research questions were developed:  
Research Design
According to Bryman & Bell (2007), a research design is used in providing a framework that is used in data analysis and data collection.  There are three types of research designs which include descriptive design, correlational design, experimental design and causal-comparative design (Cresswell & Cresswell, 2017). The following study used a descriptive design, a correlational design, and a causal-comparative design to test the various hypotheses.
A descriptive research design will be used to define the various characteristics of a variable. They include the mean, standard deviation, the median and the mode (Shuttleworth, 2008). A correlation design was also adapted to determine whether or not two or more variables are correlated. On the other hand, a causal-comparative design is used to focus on the analysis of a a specific problem so as to explain the pattern of relationship between variables.
When carrying out any research, it is paramount to gather the pertinent data which suits the research design and the methodology. Data collection can either be primary or secondary. According to Saunders (2011), primary data collection entails different methods such as observation, survey, and focus groups. The following research made us of primary data. Data were collected using questionnaires.
The sampling procedure that was used was simple random sampling. It is one of the main ways of collecting data from participants (Kothari, 2004). A simple random sample of 2,000 patrons was chosen. From the 2,000 patrons to whom surveys were sent, only 400 responded.
The study also ensured that the ethical considerations had to be considered. Ethics entails the appropriateness of a researcher behavior with regards to the right of the theme of the work which is touched on by research (Gajjar, 2013). Walker (2007) defined ethics are the term of a code of behavior which is suitable to the code of conduct of research and academics. In this study, the guidelines of ethics that were followed were keeping all the details of participants confidential and informing them completely with regards to the study’s nature. Moreover, they were given consideration that was fair and personal biases did not impede how the research was carried out, with the results being accurately represented as they were observed and told.
Hypothesis Development
To carry out the study, the following hypotheses were developed. They include:
Hypothesis 1
H0: The amount potential clients are ready to use on a meal on average is equal to $15.
HA: The amount potential clients are ready to use on a meal on average is not equal to $15.
Hypothesis 2
H0: All clients devote an average of $200 a month on food.
HA: All clients devote more or less than the average of $200 a month on food.
Hypothesis 3
H0: The anticipated monthly spending on average does not differ between prospective clients living in different zip codes.
HA: The anticipated monthly spending on average differs between prospective clients living in different zip codes.
Hypothesis 4
H0: The probability to frequent the café between people with different levels of income levels.
HA: The probability to frequent the café differs between people with different levels of income.
Hypothesis 5
H0: There is no difference between the average amount of people spend on food monthly and the price people are willing to pay for meals on average, age, and gender.
HA: There is a difference between the average amount of people spend on food monthly and the price people are willing to pay for meals on average, age, and gender.
Statistical Technique and Justification
Hypothesis 1
In order to assess hypothesis 1, a one-sample t-test was used. A one-sample t-test is the most suitable test since it associates the difference between the mean of one variable and a pre-determined mean (Ross & Wilson, 2017).
Hypothesis 2
Similarly to hypothesis 1, a one-sample t-test was adopted. Therefore, the test was appropriate since it compares the difference between the mean of one variable and a pre-determined mean (Ross & Wilson, 2017).
Hypothesis 3
To evaluate hypothesis 3, a one-way analysis of variance (ANOVA) was used. The one-way ANOVA is the most appropriate test since it determines the statistical significance between the means of two or more unrelated groups that are independent (Heiberger & Neuwirth, 2009). Moreover, to determine the specific groups’ statistical significance, a post hoc test using Tukey HSD was adopted (Ruxton & Beauchamp, 2008).
Hypothesis 4
To test hypothesis 4, the chi-square test for independence was used. The test was appropriate since it is used in discovering the presence of a relationship between two categorical variables (McHugh, 2013). The test was also used since the two groups passed the assumptions test which requires for the two variables to be categorical data (ordinal or nominal) and the groups to be independent (Test, 2015).
Hypothesis 5
To test hypothesis 5, a one-way multivariate analysis of variance (one-way MANOVA) will be used. A one-way MANOVA is the most appropriate in determining whether there is any difference between independent groups on more than one continuous dependent variable (Morrison, 2005).
Results
Hypothesis 1
A one-sample t-test was used to prove hypothesis 1. The output of the test is as shown in the tables below:
Table 1: One-Sample Statistics  
From the statistics, it is seen that the average price of the meal that one expects is $17.36 with a standard deviation of $9.72. The average expectation is higher than $15. However, to prove the hypothesis, the one-sample test has to be put into consideration.
Table 2: One-Sample Test
From the one-sample test in table 2 above, it is apparent that the test is a statistically significant difference since the p-value is less than the alpha value of 0.05. Hence, we choose to not to accept the null hypothesis and accept the alternative hypothesis. Thus, the amount clients are keen to spend on meals on the average is not equal to $15.
Table 2: Gender Report
From table 2, it is clear that the females ($17.5) were more willing to spend more on entrée course compared to the males ($17.21).
Hypothesis 2
Equally, a one-sample t-test was used to prove hypothesis 2. The output of the test is as shown in the tables below:
Table 3: One-sample Statistics
From table 3, it is apparent that the price of the meal that one spends per month in cafés is $150.05 on average with a standard deviation of $92.71. The average amount of money spent in cafés is less than $200. To prove the hypothesis, a one-sample t-test has to consider as seen in table 4 below.
Table 4: One-Sample Test
From the one-sample test in table 4 above, it is evident that the test shows a statistically significant difference since the p-value is less than the alpha value of 0.05 (Montgomery, Runger & Hubele, 2009). Consequently, we choose not to accept the null hypothesis and accept the alternative hypothesis. Thus, all patrons spend more or less than the average of $200 monthly on food.
Hypothesis 3
To prove hypothesis 3, a one-way ANOVA was chosen. The results are as shown in the subsequent tables below:
Table 5: ANOVA
From table 5, it is clear that there was a statistically significant difference between the groups as shown by the one-way ANOVA (p-value < 0.05) (Little & Rubin, 2014).  Thus, we choose to not accept the null hypothesis and accept the alternate hypothesis. Hence, the anticipated monthly spending on average differs between prospective clients living in different zip codes. Table 6: Multiple Comparison The outcomes of the Tukey post hoc test are as seen in table 6, reveal that the amount of dollars spent per month in cafes is lower in areas coded with B, C and A compared to D. Consequently, there was no statistically significant difference between the area coded with A and the area coded with D. Hypothesis 4 To prove hypothesis 4, a chi square test was used. The results are as shown in the table below: Table 7: Chi-Square Test Interpretation of the chi-square test only requires for one to focus on the Pearson Chi-Square row. It is seen that p-value < 0.05. Thus, it is evident that there is a statistically significant association between the probability to frequent a café and the diverse levels of income of the people. By choosing to not accept the null hypothesis, we can determine that the possibility to patronize the café varies between people with different levels of income. Table 8: Symmetric Measures Consequently, from table 8, it is evident that the strength of association is very strong as seen from the Phi and Cramer's V tests. Hypothesis 5 To prove hypothesis 5, a one-way multivariate analysis of variance was chosen. The results are as displayed in the subsequent tables below: Table 9: One-way MANOVA From table 9, it is unmistakable that there was a statistical difference in the amount people devote to food monthly and the average price individuals are prepared to spend on meals on the basis of age and a combination of age and gender (p < 0.05). However, there is no statistical difference in the amount potential clients use on food monthly and price people are keen to pay for meals on average on the basis of gender (P > 0.05).
Analysis and Summary of the statistical results

Dollars which potential patrons are willing to pay for a meal

From the results obtained on hypothesis 1, it was proven that the patrons are not willing to pay for a meal at $15. The patrons were willing to pay a little bit higher than $15 and would comfortably part away with $17.36 to enjoy a meal at the café. Thus, by charging $15, the price is very reasonable. Consequently, it was observed that there was a difference in the willingness to pay between males and females. The females were willing to pay a higher amount of $17.5 compared to the males who were willing to pay $17.21.

The clients devote $200 a month on food on average

Hypothesis 2 proved that the patrons spent either more or less than the monthly average of $200 on food. However, a focus on the mean difference suggests that the patrons paid less than the monthly average of $200 on food. Thus, it can be reported that the patrons spent between $140.94 and $159.17 with a 95% level of confidence. Consequently, the patrons paid $150.05 per month for food on average.

Zip code area(s) that offer the most suitable locality for the café

From hypothesis 3, it was seen that the anticipated average monthly expenditure differed between potential clients living in different zip codes. The most suitable location for the café was determined through the Tukey post hoc test. Thus, the best location would be in areas coded with D. The areas coded with A, B, and C are not the best since they are the areas in which the expected average monthly spending is low.

Prospects of patronizing the café between people with diverse levels of income

Hypothesis 4 proved that there is the prospect to frequent a café based on the different income levels of the people. On the other hand, the Phi and the Cramer’s V test showed that the strength of association between the likelihood to patronize a café and the level of income is very strong. Thus, when an individual has a high income, then he or she is more likely to patronize a café compared to an individual with a lower income.

Money spent on food on average monthly can be explicated by the amount people are willing to pay for meals on average, gender, and age

From the test on hypothesis 5, it has been seen that the average amount people devote to food monthly can be explicated by the average price potential clients are willing to spend on meals, age, and gender. Based on the Wilk’s Lambda test, there is a statistical difference in the amount people devote on food monthly and the average price people are prepared to pay for meals on the basis of age. Moreover, the difference can be seen on the basis of a combination of age and gender. However, the difference is not significant on the sole basis of gender.
Recommendations
From the results of the data analysis, it can be recommended that Gloria Jones should place her price of $15. However, to bring in more profit from the venture, the maximum price that she should target is $17.36. On the other hand, to boost her business greatly, Jones can target the female population as they were more willing to pay more compared to the male population.
It was also observed that the regulars were not prepared to expend a monthly average of $200 on food but would prefer to pay a monthly average of $150. In this regard, the expected average monthly spending was different for potential clients living in different zip codes. Thus, she needs to put up her business in an area which would bring in more business. The best location for her to put her business was in the areas coded with D (areas with postcodes ending with 10, 11 & 12).
Moreover, targeting high-income earners will make the café more popular. The study has proved that individuals with a high income are more likely to patronize a café compared to individuals with low income. Moreover, it was found out that the amount people expend on food monthly on average can be described by the average value patrons are ready to spend meals, age, and gender. Thus, Gloria should come up with an establishment that should target its customer based on their basis of age and gender. Age can be considered independently but not gender.
References
Bell, E., & Bryman, A. (2007). The ethics of management research: an exploratory content analysis. British Journal of Management, 18(1), 63-77.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Davidsson, P., & Wiklund, J. (2007). Levels of analysis in entrepreneurship research: Current research practice and suggestions for the future. In Entrepreneurship (pp. 245-265). Springer, Berlin, Heidelberg.
Gajjar, N. B. (2013). Ethical consideration in research. Education, 2(7).
Heiberger, R. M., & Neuwirth, E. (2009). One-way anova. In R through excel (pp. 165-191). Springer, New York, NY.
Kothari, C. R. (2004). Research methodology: Methods and techniques. New Age International.
Little, R. J., & Rubin, D. B. (2014). Statistical analysis with missing data (Vol. 333). John Wiley & Sons.
McHugh, M. L. (2013). The chi-square test of independence. Biochemia medica: Biochemia medica, 23(2), 143-149.
Morrison, D. F. (2005). Multivariate analysis of variance. Encyclopedia of biostatistics, 5.
Montgomery, D. C., Runger, G. C., & Hubele, N. F. (2009). Engineering statistics. John Wiley & Sons.
Ross, A., & Willson, V. L. (2017). One-Sample T-Test. In Basic and Advanced Statistical Tests (pp. 9-12). SensePublishers, Rotterdam.
Ruxton, G. D., & Beauchamp, G. (2008). Time for some a priori thinking about post hoc testing. Behavioral Ecology, 19(3), 690-693.
Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India.
Sharma, P., & Chrisman, S. J. J. (2007). Toward a reconciliation of the definitional issues in the field of corporate entrepreneurship. In Entrepreneurship (pp. 83-103). Springer, Berlin, Heidelberg.
Shuttleworth, M. (2008). Descriptive research design. Retrieved Apr, 15, 2015.
Stevenson, H. H., & Jarillo, J. C. (2007). A paradigm of entrepreneurship: Entrepreneurial management. In Entrepreneurship (pp. 155-170). Springer, Berlin, Heidelberg.
Test, O. (2015). Your chi-square test is statistically significant±now what. Pract Assess Res Eval, 20(8), 2-10.
Walker, W. (2007). Ethical considerations in phenomenological research. Nurse researcher, 14(3).

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