I need this ASAP. The Harris Poll conducted a survey in which they asked, "Do you have any tattoos?" Of the 1461 malessurveyed, 210 responded that they have tattoos. Of the 1263 females surveyed, 165 responded that theyhave tattoos.a. Construct a 97% confidence interval for the difference between the proportions of males and femaleswho have tattoos. Round your answers to 3 decimals.Critical value: %* ort*(Enter the positive one.)Margin of Error: E =Confidence Interval: [=]b. Interpret your result in part (a) in a complete sentence.YesNoc. Based on your confidence interval, can you conclude that there is a difference between theproportions of males and females who have tattoos?

given data males : n1 = 1461 x1 = 210p^1 = x1n1 = 2101461 = 0.1437female : n2 = 1263 x2 =…

Answered: The Harris Poll conducted a survey in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Your company decides to conduct some production analysis for two of its most popular brands of cups. A carton of Brand X takes 10 hours to produce and 5 hour to package. A carton of Brand Y takes 15 hours to produce and 25 hours to package. If there are exactly 300 hours per month for production and exactly 325 hours per month for packaging, complete the following questions to determine how many cartons of each type of cup will be ready for shipping using all the available time. Create a system of equations for the situation using r for Brand X of cups and y for Brand Y of cups. Equation 1: Equation 2: Graph the system of equations on the grid provided: +30+ 28 26 24 22 20 18 10 14 12 10 2. 4 8 10 12 14 16 18 20 22 24 Clear All Draw:
At inventory time, 435 pounds of magnet wire for winding motors is available. In ten successive days, 15 pounds, 6 pounds, 24 pounds, 12 pounds, 3 pounds, 8 pounds, 17 pounds, 32 pounds, 16 pounds, and 13 pounds of wire are taken out of stock. How many pounds are left?
A researcher believed that the number of rental cars in service by a car rental company would have an impact on the total annual revenue for that car rental company. Five small car rental companies were surveyed, with the number of Cars in service recorded in units of 1000 (so if a car rental company had 54000 cars in service, a 54 would be recorded) and Annual Revenue measured in millions of dollars (so an Annual Revenue of $10,000,000 would be recorded as 10). The data follows: Cars (1000s) Annual Revenue ($ millions)11.5 118 10.0 135 9.0 100 5.5 37 3.3 32 Part of the Excel-generated Simple Linear Regression output is provided below: ANOVA df SS MS F Significance F Regression 1 7891.863897 7891.863897 22.91180151 0.017339231 Residual 3 1033.336103 344.4453677 Total 4 8925.2…
There were 25 more peanut bars than chocolate bars in a candy shop. 2/5 of the chocolate bars and 3/8 of the peanut bars were sold for a day. After sales, 75 peanut bars remained. How many of both types of bars had to be replaced for the beginning of the next day’s sales?
You are the operator for a herbicides formulations plant. The specification for the herbicide that you are making is 30% active ingredient. The batch is currently at 26% active ingredient. The current batch weight is 8,400pounds. How much 50% concentrate material should you add to bring the batch up to the specification?
A researcher believed that the number of rental cars in service by a car rental company would have an impact on the total annual revenue for that car rental company. Five small car rental companies were surveyed, with the number of Cars in service recorded in units of 1000 (so if a car rental company had 54000 cars in service, a 54 would be recorded) and Annual Revenue measured in millions of dollars (so an Annual Revenue of $10,000,000 would be recorded as 10). The data follows: Cars (1,000s) Annual Revenue ($ millions)11.5 118 10.0 135 9.0 100 5.5 37 3.3 32 Part of the Excel-generated Simple Linear Regression output is provided below: ANOVA df SS MS F Significance F Regression 1 7891.863897 7891.863897 22.91180151 0.017339231 Residual 3 1033.336103 344.4453677 Total 4 8925.2 Coefficients Standard Error t Stat P-value Intercept -19.12490108 23.1658578…

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