A pom-pom manufacturer makes each of its pom-poms with 35% white strands (w), 25% blue strands (b), and 40% red strands (r). If each pom-pom has a total of 80 strands, how many of strands of each color are needed to make a pair of pom-poms? In this activity, you’ll work through this pom-pom problem step by step. Part A

Write a proportion for the number of strands in each color to find how many strands are needed to make one pom-pom.

white strands: = blue strands: = red strands: =

Part B

Solve for w, b, and r using the proportions from part A. Show your work.

Part C

How many strands of each color are required to make a pair of pom-poms? Use the values you found in part B for w, b, and r. Show your work.

Part D

You can solve the problem in part C using a different method. To set up this method, first find the total number of strands required to make a pair of pom-poms.

Part E

Now solve for w, b, and r for a pair of pom-poms using the total number of strands you found in part D. Solve three proportions similar to the work you did in Part B. Show your calculations.

Part F

Did you get the same answer in parts C and E?

What two consecutive odd integers have a sum of -28

Astudent draws two parabolas on graph paper. both parabolas cross the x-axis at (-4, 0) and (6,0). the y-intercept of thefirst parabola is (0, –12). the y-intercept of the second parabola is (0-24). what is the positive difference between the avalues for the two functions that describe the parabolas? write your answer as a decimal rounded to the nearest tenth.

1. the manager of collins import autos believes the number of cars sold in a day (q) depends on two factors: (1) the number of hours the dealership is open (h) and (2) the number of salespersons working that day (s). after collecting data for two months (53 days), the manager estimates the following log-linear model: q 4 equation 1 a. explain, how to transform the log-linear model into linear form that can be estimated using multiple regression analysis. the computer output for the multiple regression analysis is shown below: q4 table b. how do you interpret coefficients b and c? if the dealership increases the number of salespersons by 20%, what will be the percentage increase in daily sales? c. test the overall model for statistical significance at the 5% significance level. d. what percent of the total variation in daily auto sales is explained by this equation? what could you suggest to increase this percentage? e. test the intercept for statistical significance at the 5% level of significance. if h and s both equal 0, are sales expected to be 0? explain why or why not? f. test the estimated coefficient b for statistical significance. if the dealership decreases its hours of operation by 10%, what is the expected impact on daily sales?