: Quality

1. Calculate the simple linear regression model that could be used to predict gas mileage from vehicle weight using the data provided below. The table contains the vehicle weight (in pounds) and gas mileage (mpg). Also provide the value for the correlation coefficient, r. (40 points) x: Weight (lbs) y: Mileage (mpg) 3,000 18 2,800 21 2,100 32 2,900 17 2,400 31 3,300 14 2,700 21 3,500 12 2,500 23 3,200 14 2. Managers at JRPS hold regular Monday morning meetings to discuss sales and production. At this meeting, one topic has been often discusses: shop scheduling. Shop scheduling is a key process critical to customer satisfaction. A well-scheduled shop means that product can be produced in time to meet customer due dates. It also means that the workload is realistic for employees. Unfortunately, the shop schedule has not been easy to arrange. JRPS decided to make a multi-vari chart to depict the variation present in the sales process. A multi-vari chart will allow them to study within-month and between-month variation. Each month, sales are tracked for the beginning of the month, mid-month, and end of the month as given in the table below. Create a multi-vari chart using this data for JRPS. (40 points) Beginning Middle End January 325,000 400,000 590,000 February 410,000 610,000 650,000 March 450,000 500,000 700,000 April 415,000 525,000 600,000 May 500,000 625,000 650,000 June 400,000 450,000 500,000 July 700,000 650,000 500,000 August 610,000 600,000 430,000 September 650,000 655,000 725,000 October 400,000 610,000 650,000 November 550,000 650,000 720,000