A business could be experiencing challenges in a specific market or finds that it has fully exploited its market may want to expand into new markets. The expansion into new markets opens up new opportunities which entrepreneurs will be interested in. The new market presents an opportunity for new customers where a business is going to reach a new group of customers. The new market will be used to establish a new source of revenue streams and this can take place through an improvement in the company’s sales (Noe et al., 2017). However, the expansion into the new market is not going to be something easy. A business should understand the new market adequately in order to ascertain that the new market will be the best decision and the best step for the company. For the present analysis, Big D is an outdoor sporting goods client wants to expand to Chicago. This case study involves an analysis of Big D as it expands to Chicago analyzed by formulating a chi-square test and hypothesis testing.
Big D Case Scenario
The given scenario involves Big D, a company that participates in business and outdoor services. There is a need for the company to expand its business through diversification. The need for diversification has been acknowledged through the completion of the company’s previous projects. There are factors that should be considered when a business is expanding into new markets include occupational, employment, the household income, educational attainment, ethnicity, and population of the proposed new destination.
Delegate your assignment to our experts and they will do the rest.
Big D has been running its business in the United States and would like to open new locations to Chicago. From the observations, Chicago presents a prime opportunity for the business because it has high literacy levels, a high household income, has experienced an increase in its owner occupation in housing, a higher median household income, and higher employment for consumers compared to the average of the United States. From the analysis, Chicago offers a viable region where Big D Incorporated can invest. The region offers a huge potential for profitability as it is expected that most of the consumers have a higher purchase potential.
Present Case Scenario
The present case scenario, as a Business Analyst for Big D Incorporate, one should make recommendations that are addressed to the Board of Directors regarding the new opportunity. The recommendation provided should be based on data that is calculated by using statistical formulas that are appropriate. The interpretation of the given statistical data should be used to make appropriate recommendations. The key tools that have been identified to conduct the statistical analysis involve the formulation of a full Chi-square that will help in making the decision for the outdoor sporting goods client. A null hypothesis and an alternative hypothesis will also be used to present the justification of the selection.
Chi-Square Test
The chi-square test is usually used to determine if there will be a significant difference between the expected and observed frequencies for variables in different categories. It is used to determine whether the individuals or numbers which fall within a category will differ significantly from the number that is expected. Chi-square tests have several requirements that include quantitative data, data in a frequency form, having several categories, independent observations, an adequate sample size, and a simple random sample (Kim, 2017).
Test Methodology
The test methodology for the chi-square test should be done by following a series of procedures that include expressing the null and alternative hypothesis, determination of the significance level, calculating the chi-square test statistic, and testing the procedures (Moore, 2017). The null hypothesis states that the characteristic does not affect the response while the alternative hypothesis states that the response is affected by the characteristic. The significance level Alpha (α) is set at 5% (0.05). A p-test can then be carried out by considering the chi-square table. A value that is higher than that in the table will mean rejecting the null hypothesis while a value that is lower will imply accepting the null hypothesis (Bozeman Science, 2011).
A non-parametric, also known as distribution-free test, will be used when conducting the chi-square test analysis. Non-parametric sample sizes are usually used when the variables are measured on an ordinal or nominal scale. While the chi-square is appropriate for the unequal or equal sizes of the groups, a non-parametric test will address only the equal sample sizes of the given groups. Additionally, non-parametric tests will be applicable when the studied data violates the assumptions of normality.
Chi-Square Analysis for Big D Inc.
Big D incorporated incorporates two variables; the indoor sporting goods and the outdoor sporting goods. The chi-square test will be used for Big D Incorporated to test for independence between two related variables. The chi-square makes reference to the categorical and nominal data to find the associates between the different variables. The application of the Chi-square for Big D will be used to check whether the variables that are under study have a relationship or are independent of each other.
Hypothesis formulation:
The null hypothesis and alternative hypothesis for Big D Incorporated will be incorporated to show the relationship and variation between the variables. The null hypothesis will state that there is no significant variation between indoor sporting goods and outdoor sporting goods production frequencies. The alternative hypothesis will indicate that there is a significant variation between the outdoor sporting production and the indoor sporting production. The contingency table for the Chi-square for Big-D will be as shown in the table 1.
Chi-square Test for the New Market
The chi-square test will be important in evaluating the viability of the new market. However, there is insufficient data about the core competencies of the company. The approach that will be used for the analysis will involve the gathering of data about the general actual market in the United States. The expected values will involve the income of the residents in Chicago. The actual and expected variables will be used to conduct the evaluation.
There is a need to conduct research for the business expansion of Big D. For the research to be conducted, the actual and expected frequency will be incorporated when performing the analysis. The general counts of data to be conducted will involve income by type earnings in the United States. The given variables to be used to conduct the chi-square test are the actual and expected variables. The actual variable will involve the total observed data of income by type earnings in the United States population. The expected variable will involve the total observed data of income by type earnings expected in the Chicago population.
Hypothesis formulation
The hypothesis will be formulated as:
Null Hypothesis: There is no significant variation between the actual United States income and expected Chicago income.
Alternative Hypothesis: There is a significant variation between the actual United States income and the expected Chicago income.
Data Analysis
The observed values were taken from the data of the United States regarding the income by type earnings for the population of the United States. The expected values were formulated based on the expected income by type earnings for Chicago. If there would be no significant difference between the expected and actual income, then Chicago would be viable for business expansion.
The Chi-square test was conducted by using the tool “CHISQ.TEST( actual values , expected values )” available on Microsoft Excel. The data was entered accordingly and the test returned a value of zero. The value of zero which was below 10.85 for 20 categories. The result from the p-value indicated strongly that the null hypothesis should be accepted. This implied that there was no significant difference between the observed and expected counts of income within the Chicago population (expected) and the United States population (observed). The observation shows that Big D Incorporated should thus expand its business to Chicago because it is a high prime area that will offer a conducive environment for the growth of the company.
Conclusion
Big D is a company that sees the need of expansion of its business operations to other parts of the United States. The location that has been identified for expansion by Big D is in Chicago. The place has a high employment rate, high per capita income, a large population, and a high literacy ratio. Chi-square test is a statistical tool that can be used test show the relationship between two variables. A 95% statistical significance of 95% was used to conduct the test. From the analysis, there was no significant difference between the expected income values of Chicago and that of the United States. Chicago is also expected to have a higher per capita income compared to the average of the United States. The expansion to Chicago is thus viable for Big D and will work to advance the company’s sales and revenues.
References
Bozeman Science. (2011, November 13). Chi-squared test [Video file]. Retrieved from https://www.youtube.com/watch?v=WXPBoFDqNVk
Kim, H. Y. (2017). Statistical notes for clinical researchers: chi-squared test and Fisher's exact test. Restorative dentistry & endodontics , 42 (2), 152-155.
Moore, D. S. (2017). Tests of chi-squared type. In Goodness-of-fit-techniques (pp. 63-96). Routledge.
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2017). Human resource management: Gaining a competitive advantage . New York, NY: McGraw-Hill Education.
