Click on the datafile logo to reference the data. Let us consider an example involving Espléndido Jugo y Batido, Inc. (EJB), a company that manufactures bottled juices and smoothies. EJB produces its products in five fruit flavors (apple, grape, orange, pear, and tomato) and four vegetable flavors (beet, carrot, celery, and cucumber), and it ships these products from distribution centers (DCs) in Idaho, Mississippi, Nebraska, New Mexico, North Dakota, Rhode Island, and West Virginia. EJB management has retrieved data on each order it has received over the past three years and stored it in a data file. Each record in the data corresponds to the amount of one product (a combination of category and flavor) included in a single order, so an order can consist of multiple records in the data. Each record in the data provides the following. Order ID flavor category (juice or smoothie) dollar amount sold date ordered date delivered DC that filled the order an indication on whether the order was received from a new customer service satisfaction rating reported by the customer product satisfaction rating reported by the customer Within the chapter, univariate analysis was demonstrated on some of the variables. We continue this analysis in this problem. (a) Using a PivotChart, construct the relative frequency distribution of records over the values of the Category variable. Describe your findings. (Enter your answers in percent. Round your answers to two decimal places.) Juices make up % of total orders, and smoothies make up % of total orders. (b) Using a PivotChart, construct the relative frequency distribution of records over the values of the New Customer variable. In the PivotTable, relabel a "No" value for New Customer as "Existing" and a "Yes" value as "New." Describe your findings. (Enter your answers in percent. Round your answers to two decimal places.) Existing customers make up % of all orders, and new customers represent % of all orders.