• 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 To understand the implications of missing data, we must explore the patterns associated the missing entries for the Product Satisfaction Rating variable in the EJB data. Click on the datafile logo to reference the data. DATA file (a) Construct the relative frequency distribution of records over the values of the Product Satisfaction Rating variable. What percentage of records are missing a value of Product Satisfaction Rating? (Round your answer to two decimal places.) 53.21 % (b) Considering only records that report values of Product Satisfaction Rating, construct the relative frequency distribution of records over the different flavors. Next, considering records that are missing values of Product Satisfaction Rating, construct the relative frequency distribution of records over the different flavors. Compare these distributions. What does this comparison suggest? (Enter your answers in percent. Round your answers to two decimal places.) The flavor that shows the largest difference in percentages between these two distributions is orange Product Satisfaction Rating, % were this flavor, and of the records that didn't report a value, This suggests that the tendency of an order to be missing a product satisfaction rating is . Of the records that reported values of % were this flavor. affected by whether the order involves this flavor.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Transcribed Image Text:• 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 To understand the implications of missing data, we must explore the patterns associated the missing entries for the Product Satisfaction Rating variable in the EJB data. Click on the datafile logo to reference the data. DATA file (a) Construct the relative frequency distribution of records over the values of the Product Satisfaction Rating variable. What percentage of records are missing a value of Product Satisfaction Rating? (Round your answer to two decimal places.) 53.21 % (b) Considering only records that report values of Product Satisfaction Rating, construct the relative frequency distribution of records over the different flavors. Next, considering records that are missing values of Product Satisfaction Rating, construct the relative frequency distribution of records over the different flavors. Compare these distributions. What does this comparison suggest? (Enter your answers in percent. Round your answers to two decimal places.) The flavor that shows the largest difference in percentages between these two distributions is orange Product Satisfaction Rating, % were this flavor, and of the records that didn't report a value, This suggests that the tendency of an order to be missing a product satisfaction rating is . Of the records that reported values of % were this flavor. affected by whether the order involves this flavor.

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