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- You are given the following dataset from a sample of the population. Superhero Number of Villains Captured Number of Losses Average Hours of Sleep Spiderham 30 9 12 Alligator Loki 50 1 23 Iron Man 20 8 6 Phil Coulson 18 2 8 Yelena Belova 25 5 2 Round all answers to 2 decimal places. IE: 3.567 = 3.57 A. What kind of dataset is this? Answer either Panel, Time series, or cross sectional B. Calculate the average number of villains captured in this sample. C. Calculate the variance of the number of villains captured in this sample. D. Calculate the correlation between the number of villains captured and average hours of sleep . If answer is negative, include negative sign. E. Calculate the sample covariance between the average number of losses and average hours of sleep . If answer is negative, include negative sign.A survey of 800 college seniors resulted in the following crosstabulation (Table 1) regarding their undergraduate major and whether or not they plan to go to graduate school. Please use the information to answer questions 1-3. Undergraduate Major Graduate School Business Engineering Others Total Yes 70 84 126 280 No 182 208 130 520 Total 252 292 256 800 1.What percentage of the students does not plan to go to graduate school? 2.What percentage of the students' undergraduate major is engineering? 3.Of those students who are majoring in business, what percentage plans to go to graduate school?here is a 2 question and data to answer this question.
- What is the relationship between the $ price of paint and the gallon demand for this paint? A random sample of (price, quantity) data for 7 days of operation was obtained. Construct a plot and describe the relationship between quantity and price, with emphasis on any unusual observations.(10, 100) (8, 120) (5, 200) (4, 200) (10, 90) (7, 110) (6, 150)3Q2Q3: Both questions correlate with each other. Use the following to complete the graph.Read the executive summary thoroughly and attempt the questions given below:The prevailing of fast food consumption and obesity in Iranian student is high. Fast food consumptionwas associate with abdominal obesity based on WHR, but did not has related to general obesity basedon BMI. In an analytical cross-sectional study, 300 students were selected random from the twolargest universities in Qom, center of Iran, studying in medical and basic sciences fields in 2015. Isuccessfully collected the data by a modified version of NELSON’S fast food questionnaire andanthropometric measures including Waist-Hip Ratio (WHR) and Body Mass Index (BMI). Chi-square,independent t-test, and multivariate logistic regression were used for statistical analysis. I want toestimate the prevalence of fast food consumption and to assess its association with abdominal andgeneral obesity. My results has shown that, 72.4% (67.4% in females vs 80.7% in males) had at leastone type of fast food consumption in the…
- Q. Please draw a graph as indicated in the problem and answer the question The data presented in Table were published in the March 1, 1984, issue of The Wall Street Journal. They relate to the advertising budget (in millions of dollars) of 21 firms for 1983 and millions of impressions were retained per week by the viewers of the products of these firms. The data are based on a survey of 4000 adults in which users of the products were asked to cite a commercial they had seen for the product category in the past week. a. Plot impressions on the vertical axis and advertising expenditure on the horizontal axis. b. What can you say about the nature of the relationship between the two variables? c. Looking at your graph, do you think it pays to advertise? Think about all those commercials shown on Super Bowl Sunday or during the World Series. Please provide an explanation in detail as well.Twenty different statistics students are randomly selected. For each of them, their body temperature (°C) is measured and their head circumference (cm) is measured. a. For this sample of paired data, what does r represent, and what does ρ represent? b. Without doing any research or calculations, estimate the value of r. c. Does r change if body temperatures are converted to Fahrenheit degrees? Question content area bottom Part 1 a. Choose the correct answer below. A. r is a parameter that represents the value of the linear correlation coefficient that would be computed by using all of the paired data in the population of all statistics students, and ρ is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data. B. r is a statistic that represents the proportion of the variation in head circumference that can be explained by variation in body temperature, and ρ is a parameter that represents…this question has not been graded i am trying to get help with it. it is a macroeconmics question
- We have a random sample of workers from a large firm. In 2017, the firm ran a training program. Some workers did the training program, others did not. The firm now wants to assess the effect of the training on earnings. We use the following model to estimate the effect of a training program on annual earnings in 2018: ln(earn2018)=β0+β1train+β2ln(earn2016)+β3educ+β4exper+u where earn2018 = individual total annual earnings in 2018 in dollars train = a dummy variable that takes the value 1 if the individual worker did the training in 2017 and 0 otherwise earn2016 = individual total annual earnings in 2016 in dollars educ = the individual's years of education exper = the individual's years of experience We find: ln(earn2018)^= 11.672 + 0.041train + 0.821ln(earn2016) + 0.037educ + 0.012exper (5.864) (0.019) (0.258) (0.013) (0.007) n=1278, R2= 0.048 Which of the following is the correct interpretation of the…We have a random sample of workers from a large firm. In 2017, the firm ran a training program. Some workers did the training program, others did not. The firm now wants to assess the effect of the training on earnings. We use the following model to estimate the effect of a training program on annual earnings in 2018: ln(earn2018)=β0+β1train+β2ln(earn2016)+β3educ+β4exper+u where earn2018 = individual total annual earnings in 2018 in dollars train = a dummy variable that takes the value 1 if the individual worker did the training in 2017 and 0 otherwise earn2016 = individual total annual earnings in 2016 in dollars educ = the individual's years of education exper = the individual's years of experience Now, I want to test whether the effect of an additional year of education increases earnings by twice as much as an additional year of experience. My null hypothesis is H0:β3=2β4. To get the standard error I need to conduct this hypothesis test, I rearrange or re-parameterise…Residents in one housing development were asked a series of questions by their homeowners’ association. Identify the type of data for each question.a. Did you play golf during the last month on the development’s new golf course?b. How many times have you eaten at the country club restaurant during the last month?c. Do you own a camper?d. Rate the new security system for the development (very good, good, poor, or very poor).