Example 1: Linear Programming Applications A refinery must produce at least 100 gallons of gasoline and at least 160 gallons of diesel to meet customer demands. The refinery would like to minimize the cost of crude. Two crude options exist. The less expensive crude costs $80 per barrel while a more expensive crude costs $95 per barrel. Each barrel of the less expensive crude produces 10 gallons of gasoline and 20 gallons of diesel. Each barrel of the more expensive crude produces 15 gallons of both gasoline and diesel. 1. Formulate a linear programming model to find the number of barrels of each crude that will minimize the refinery cost while satisfying the customer demands.

Q: The sum of two times a number and twenty-two?

A: Given :   The sum of two times a number and twenty-two

Q: Solve                 2   =   X-500/ 85

A: Firstly, we add 500/85 on both sides  and then by adding 2+500/85, we get the required result.

Q: Six more than the quotent of a number and 4 is 8.

A: let that number is x and quotient of the number and 4 be x4

Q: Solve  5x =-5 3

A: Solve  5x =-5 3

Q: –+l l5=405 %3D

A: We can solve the quinary number system problem as below.

Q: Find the value of the variable -5x = -5

A: Given equation is -5x=-5. To find the value of the variable. Solution: Multiplying both sides of…

Q: Solve exactly: ex-4 = 6

A:

Q: Solve 3*+1=9*=27

A:

Q: Solve ex =-x

A:

Q: number

A: Given: 2 times a number is equal to -5 times 3. To find: A number.

Q: 42

A: We have to solve given equation for y.

Q: ax-1 = 81 solution set =

A: Given query is to find the value of x.

Q: The sum of two consecutive integers is 41. What are the integers?

A: Let the first integer = x Let the second integer = x +1

Q: What is one less than twice a number

A:

Q: Find the value of the variable 7x = -35

A: Find the value of the variable 7x = -35

Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.