Tableau Case Study Solution

Other variables that we plugged into Tableau to get a breakdown of how they affected sales volume per city were working women with children, and non-working women with children. Hypothetically speaking, these variables sparked our interest because it is intriguing to think about how the levels of stress from having kids and working could potentially influence someone to purchase alcohol. Initially when we ran our regression model the coefficient for the percent of working women with children was -2,531. This means that as the percentage of women working with children increases by 1, the weekly sales volume decreases by 2,531. Even though this was not a significant variable in our model, the graph from Tableau showed us that there were was a trend that confirmed the understanding we drew from …show more content…
In this graph we included the percent of households with 5 or more persons (hhlarge), percent of households with 1 person (hsize1), and the percent of households with 3 or 4 persons (hsize34). Each bar represents the household variables while the number at the end of each bar is the weekly average sales volume for each city. Per the graph, Chicago had the highest weekly average sales volume at 8,075 and also had the largest percentages of each household type. Households with one person reached almost 6% for Chicago in comparison to households with 3 or 4 persons at roughly 5%, and households with 5 or more persons reaching about 2.2%. By examining these visuals we drew the general conclusion that on average each city tends to have the highest percent of households with 3 or 4 persons while a household of one person is the lowest. Overall though, there is no direct relationship that can be drawn comparing household size and weekly average sales volume. Each city is different and there seems to be no overall trend showing that one household size causes weekly sales to increase or