A consulting firm conducted an experiment to analyze how wor…

A consulting firm conducted an experiment to analyze how work arrangement and manager support type impact task completion time for a standardized data-reporting task. They used a 3×4 factorial design: Factor A – Work arrangement In-office Hybrid Fully remote Factor B – Manager support type No support Weekly check-ins On-demand assistance (Slack availability) Dedicated mentor during the task A total of 5 employees were randomly assigned to each combination and completed the same task. The response variable was the time it took to finish the task (in minutes). The data is shown below. No support Weekly check-ins On-demand assistance Dedicated mentor In-office 61 56 49 43 In-office 59 55 48 42 In-office 64 57 46 44 In-office 60 54 47 43 In-office 62 56 48 42 Hybrid 69 60 52 46 Hybrid 70 58 51 45 Hybrid 66 59 50 47 Hybrid 68 60 49 45 Hybrid 67 61 52 46 Fully remote 74 64 55 49 Fully remote 73 65 54 48 Fully remote 76 63 56 50 Fully remote 75 64 55 48 Fully remote 72 66 53 49 Conduct an ANOVA. Use a level of significance (alpha) of 0.05. What is the F-statistic for the Work Arrangement main effect? Round to one decimal place [a] What is the F-statistic for the Support Type main effect? Round to one decimal place [b] What is the F-statistic for the interaction between Work Arrangement and Support Type? Round to one decimal place [c]

An insurance company conducted a study to compare subscriber…

An insurance company conducted a study to compare subscriber satisfaction across three different customer support models: (1) phone-only support, (2) online chat support, and (3) AI-based virtual assistant. Two hundred subscribers were recruited for this experiment. Each subscriber was randomly assigned to one of the support models during their inquiry and then asked to rate their satisfaction on a 1 to 10 scale. The mean ratings were analyzed using ANOVA. a) What is the response variable. [a]  b) What is the number of treatments. [b]