Write an equivalent expression

Part one: measurements 1. measure your own height and arm span (from finger-tip to finger-tip) in inches. you will likely need some from a parent, guardian, or sibling to get accurate measurements. record your measurements on the "data record" document. use the "data record" to you complete part two of this project. name relationship to student x height in inches y arm span in inches archie dad 72 72 ginelle mom 65 66 sarah sister 64 65 meleah sister 66 3/4 67 rachel sister 53 1/2 53 emily auntie 66 1/2 66 hannah myself 66 1/2 69 part two: representation of data with plots 1. using graphing software of your choice, create a scatter plot of your data. predict the line of best fit, and sketch it on your graph. part three: the line of best fit include your scatter plot and the answers to the following questions in your word processing document 1. 1. which variable did you plot on the x-axis, and which variable did you plot on the y-axis? explain why you assigned the variables in that way. 2. write the equation of the line of best fit using the slope-intercept formula $y = mx + b$. show all your work, including the points used to determine the slope and how the equation was determined. 3. what does the slope of the line represent within the context of your graph? what does the y-intercept represent? 5. use the line of best fit to you to describe the data correlation.

What is the area of the triangle 10 13 12

Amachine that produces a special type of transistor (a component of computers) has a 2% defective rate. the production is considered a random process where each transistor is independent of the others. (a) what is the probability that the 10th transistor produced is the first with a defect? (b) what is the probability that the machine produces no defective transistors in a batch of 100? (c) on average, how many transistors would you expect to be produced before the first with a defect? what is the standard deviation? (d) another machine that also produces transistors has a 5% defective rate where each transistor is produced independent of the others. on average how many transistors would you expect to be produced with this machine before the first with a defect? what is the standard deviation? (e) based on your answers to parts (c) and (d), how does increasing the probability of an event a↵ect the mean and standard deviation of the wait time until success?