Which of the following is an example of "Brain Drain"? O The loss of highly skilled or educated workers O The loss of educational opportunities in a region O One of the main push factors for the United States The main reason behind forced migration
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- Analysing passenger car sales by brands in Australia Tupps Motors which was established in year 2000, sells 5 brands of new passenger vehicles Holden, Toyota, Ford, Mitsubishi and Nissan which were the market leaders in 2000. As years passed the General Manager of Tupps Motors, Brian Tupps, noticed that brands such as Holden, Ford and Nissan are not selling as much as they used to. In 2018, Brian Tupps discusses his observation with his recent Business graduate son, Ben Tupps, and they both decided to collect Australia-wide sales data of the top 10 brands of passenger vehicles in 2018 to see how the market share of the different brands have changed. Again, in 2023, Brian wanted Ben to analyse the Australia-wide post-pandemic sales data for 2022 and provide him with up-to-date advice on the market share of the 10 brands of passenger vehicles. Data on the number of passenger vehicles sales for the top 10 brands of passenger vehicles in 2018 and 2022 are provided in file 1Sales.xlsx.…NC Ch The Holcombe family went out to dinner. • The meal cost $54.65. • The sales tax is 8% of the meal. • The tip was 18% of the meal and tax. • There are 5 people in the Holcombe family.The chart below shows the price of oil ($ per barrel) between Feb 22 and Mar 7, 2022. FRED - Crude Oil Prices: West Texas Intermediate (Wm) - Cushing, Oklahoma 120 115 110 105 100 95 2022-00-22 2022-02-24 2022-02-26 2002-02-28 2002-03-02 2022-03-04 2022-03-06 Part (a) Explain the qualitative shift between February 22 and March 7 using standard supply and demand analysis. Part (b) The following table shows oil production in 2020 of the top-ten oil-producing countries. For reference: Total world oil production in 2020 was approximately 76,000,000 barrels (bbl)/day. Oil production Country 2020 (bbl/day)l1) United States 11,307,560 2 Russia 9,865,495 3 Saudi Arabia (OPEC) 9,264,921 4 11 Canada 4,201,101 5 Iraq (OPEC) 4,102,311 | China 3,888,989 6 United Arab Emirates (OPEC) 3,138,249 7 8 | Brazil 2,939,950 9 Iran (OPEC) 2,665,809 10 Kuwait (OPEC) 2,625,145 What is the approximate magnitude of the price change displayed in part (a)? Explain how this price change is quantitively consistent…
- C2. The following cross-tabulation, based on GSS18SSDS-B data, examines the relationmchia between age (the independent variable) and presidential candidate one voted for in the 2016 U.S. presidential election (dependent variable). Notice we have recoded age into four categories: 18–29, 30–39, 40–49, and 50–59. Respondents of all other ages have been excluded from the analysis. your ages Vote Clinton or Trump * RE AGE Crosstabulation RE AGE 18-29 30-39 40-49 50-59 Total Vote Clinton Count 65 96 77 78 316 Clinton or Trump % within RE_AGE 65.7% 61.1% 53.8% 45.6% 55.4% Trump Count 19 42 55 86 202 % within RE_AGE 19.2% 26.8% 38.5% 50.3% 35.4%3The Bureau of Labor Statistics provides the following data about U.S. workers ages 16 and older who were paid hourly rates in 2021. The table shows, overall and separately for men and women, the number of workers (in thousands, so that the upper left value of 76,125 represents over 76 million individuals) who were paid hourly that year and the number who earned the federal minimum wage or less. Characteristic Total, 16 years and older Men, 16 years and older Women, 16 years and older Number of workers (in thousands) Total paid hourly rates 76,125 38,089 38,036 At or below minimum wage 1,091 398 693 Express the value "693 thousands" in the table (lower right cell) as a sentence in context. There are 693 women 16 years and older who earned the federal minimu, wage or less. Fill in the blanks with the appropriate supporting evidence computed from the data table. Give all numerical answers as a number between 0 and 1, rounded to 3 decimal places (for ex., 0.111, no text). A U.S. worker…
- Beryllium disease: Beryllium is an extremely lightweight metal that is used in many industries, such as aerospace and electronics. Long-term exposure to beryllium can cause people to become sensitized. Once an individual is sensitized, continued exposure can result in chronic beryllium disease, which involves scarring of the lungs. In a study of the effects of exposure to beryllium, workers were categorized by their duration of exposure (in years) and by their disease status (diseased, sensitized, or normal). The results were as follows: Duration of Exposure 5 Diseased 15 7. 19 Sensitized 12 22 14 Normal 66 145 197 Send data to Excel Test the hypothesis of independence. Use the a = 0.10 level of significance and the P-value method with the TI-84 Plus calculator. What do you conclude?13. Does income increase when you get married? To investigate this, a college student has randomly selected people from his college town and collected income data for these people. They were categorized according to their marital status. The following results (in thousands of dollars) were obtained. ? Marital status Income ($1000) Income ($1000) Income ($1000) Income ($1000) Income ($1000) Married 136 116 82 166 72 Not married 33 78 76 125 80 Use the Wilconxon signed-rank test to determine if the income for married people has values that are systematically larger than for unmarried people. Perform on the 5% level (α = 0.05). What is your conclusion? (10p) A complete answer should be given that is easy to follow step by step.7. Predicting Atlanta Commute TimeThe data in CommuteAtlanta show information on both the commute distance (in miles) and time (in minutes) for a sample of 500 Atlanta commuters. Suppose that we want to build a model for predicting the commute time based on the distance. Distance Time 10 15 45 60 12 45 4 10 15 30 33 60 15 45 4 10 25 25 1 15 22 45 50 50 10 15 30 30 10 30 12 20 2 5 25 45 7 20 8 20 10 20 30 40 23 30 20 40 7 25 3 8 5 15 6 20 45 45 35 35 25 40 15 20 17 20 50 50 10 10 30 45 10 10 20 20 5 5 4 7 21 40 12 30 5 10 32 32 10 40 12 20 35 45 31 70 3 10 22 45 20 30 30 30 20 30 50 50 7 7 8 20 11 30 25 60 15 27 1 1 10 13 25 35 15 15 10 30 24 25 10 20 2 10 5 15 32 32 10 10 12 20 18 20 7 15 30 35 30 30 2 28 3 6 3 15 0 5 20 30 23 35 50 60 20 30 25 50 3 5 10 10 20 30 16 35 1 3 20 25 25 30 20 45 101 180…
- Household Income Profile of the 400 Households in a Community in 1999 Household Income Category Under $20,000 $20,000 to $29,999 $30,000 to $39,999 $40,000 to $49,999 $50,000 to $99,999 $100,000 to $299,999 $300,000 to $499.999 $500,000 and over Number of Households 30 70 90 110 80 10 5 If 3 different households of the 400 are to be chosen at random for a marketing survey, which of the following is closest to the probability that all 3 households chosen had incomes of $50,000 or more in 1999? 0.0001 0.001 0.005 0.015 0.045 If no two households in the community had the same income, and if the greatest household income had the greatest percentile ranking, which of the following could have been the income at the 85th percentile ranking of the 400 household incomes? $48,250 $79,350 $105,600 $345,750 $841,150 Select one answer choice.Risk of Stroke (%) Age Pressure Smoker (Yes=1) 12 57 152 0 24 67 163 0 13 58 155 0 56 86 177 1 28 59 196 0 51 76 189 0 18 56 155 1 31 78 120 0 37 80 135 1 15 78 98 0 22 71 152 0 36 70 173 1 15 67 135 1 48 77 209 0 15 60 199 0 36 82 119 1 8 66 166 0 34 80 125 1 3 62 117 0 37 59 207 1 1. Interpret regression coefficient of Age (b1), Pressure (b2), and Smoker (b3), respectively. 2. The regression coefficient of Age (b1) are different in the estimated simple regression equation and estimated multiple regression equation. Can you explain why? 3. If we choose the significance level α=0.05, is the variable Smoker a significant factor in explaining the risk of a stroke? Explain.fill in blanks.
