Check My Work NO eBook Thirty-three percent of all Americans drink bottled water more than once a week (Natural resources Defense Council, December 4, 2015). Suppose you have been hired by the Natural Resources Defence Council to investigate bottled water consumption in St. Paul. You plan to select a sample of St. Paulites to estimate the proportion who drink bottled water more than once a week. Assume the population proportion of St. Paulites who drink bottled water more than once a week is 0.33, the same as the overall proportion of Americans who drink bottled water more than once a week. Use z-table. a. Suppose you select a sample of 540 St.Paulites. Show the sampling distribution of (to 4 decimals). E()= = 0.33 σ = 0.0202 b. Based upon a sample of 540 St. Paulites, what is the probability that the sample proportion will be within 0.05 of the population proportion (to 4 decimals). probability = 0.9867 c. Suppose you select a sample of 250 St.Paulites. Show the sampling distribution of (to 4 decimals). E(p) = = 0.33 σ =0.0297 στ d. Based upon a smaller sample of only 250 St. Paulites, what is the probability that the sample proportion will be within 0.05 of the population proportion (to 4 decimals). X probability == 0.9077 e. As measured by the increase in probability, how much do you gain in precision by taking the larger sample in parts (a) and (b) rather than the smaller sample in parts (c) and (d)? Reduced by 0.0870 Have gain in precision by increasing the sample. 80 F3 000 000 F4 % MacBook Air F5 F6 & F7 F8 F9 FIO C C

Help with the last two questions... can't come up with an answer

Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,815.11 +2563.46 (Education) +897.49(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer Tables Keypac Keyboard Shortcu

Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,135.60 + 2525.21( Education 7.35(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer +1047.35 Tables Keypad Keyboard Shortcuts

cipate worth S Exercise 2.9.8. [S][Section 2.1][Goal 2.1][Goal 2.5] Counting red blood cells. On page 240 of the April 2011 issue of the Bulletin of the American Mathematical Society Misha Gromov wrote that Erythrocytes are continuously produced in the red bone marrow of large bones... at the rate ~ 2.5 million/second or~ 200 billion/day. Adult humans have 20-30 trillion erythrocytes,~ 5 million/ cubic millimeter of blood. [R54] (a) What is an erythrocyte? (b) Check that 2.5 million/second is about 200 billion/day. (c) Use the numbers in the second sentence to estimate the volume of blood in an adult human, in liters. (d) Check your answer to the previous question with a web search.

Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,896.07 + 2755.34 (Education) + 773.89 (Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8.years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make?

What does February 2020’s actual warehouse club sales value tell us about the strength of this model to extend past the ten years covered in the scatterplot?​ ​

Questions 1 and 2 only please. Thankyou!

Explain the various concepts & tools of regression with time series data?

When you are deciding which variables to include as predictors in a multiple regression equation, what are some conditions that you must consider first?