These are questions to consider but you dont necessarily have to use them when responding to the student

items you found to be compelling and enlightening. To help you with your discussion, please consider the following questions:

• Do you agree with your classmate's decision? Why or why not?
• What additional questions do you have after reading the posting?
• What clarification do you need regarding the posting?
• Why do you feel your decision would make more sound financial and business sense?

Student paper down below:

Big D Incorporated has worked through phase one, which consisted of analyzing qualitative and quantitative attributes. In phase two, they compared the U.S. and Chicago’s 2000 census. This helped the company understand where the new market would be. They were able to compare Chicago’s numbers with the U.S. and see what the differences are between the two. In phase three, they were able to analyze the Chi-square distribution tool, hypothesis testing, and nonparametric testing. We were able to understand what each was and how to use them to help decide if Big D should expand into the new market.

In order for Big D to make a decision, they need to identify a few independent variables. These variables include income, education level, and household size. These are some of the variables that should be utilized. The company needs to understand where their target markets income stands. If a majority of the population does not have the income, then business is going to be harder to support than higher income areas. Education level also can have an impact on if a company expands to a new area. If a larger majority of the population has graduated high school, that percentage will have an easier time finding jobs, which will help boost income. When you look at house hold sizes, those with children may have children who play sports. This helps when it comes to looking at the market with families. There are however a few factors that can impact the variables. This can include weather in the area, any major life events, promotions, or any kind of disruption, good or bad, that has some effect on the variables.

We can use different methods to help the company with making their final decision as to whether or not to expand the company into the new market. Linear regression is “a basic and commonly used type of predictive analysis. The overall idea of regression is to examine two things: 1) does a set of predictor variables do a good job in predicting an outcome (dependent) variable? 2) Which variables in particular are significant predicators of the outcome variable, and in what way do they-indicated by the magnitude and sign of the beta estimates- impact the outcome variable?” (Statistics Solutions, 2018). General linear Model is “a useful framework for comparing how several variables affect different continuous variables” (Statistics how to, 2018). These models help to determine what’s going to drive demand in the new market. This will help the company understand who their target market is and how they can target them in a successful way. This helps the company manage the business decision making when it comes to the marketing support. The Regression analysis is going to be the best method to determine how the variables will affect each other.

There are many other variables that should be taken into effect when making this type of decision. The company should look at the total population of the market they are considering. A high number for the population means more potential buyers in the market. They should analyze any existing competitors in the market as well. The need to look at who they will have to compete against, how they are promoting their products, and decide if they can compete with the competitors. They need to analyze the shopping patterns of the people in the new market. They need to determine if Sporting goods equipment is in high demand in the market. If there is not a high demand for sporting goods equipment in the new market, then the company is taking a high risk by going into the market. Employment rates in the market are also important. These rates affect business. High employment rates mean higher product demand due to increased income. By combining all of the data from these, the company can determine if they should expand into the new market or if it is too big of a risk to take.