(b) Determine what type of function best models the data. o linear O power O quadratic O cubic O quartic (c) Find the equation that is the best fit for the data. (Round all numerical values to four decimal places.)
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B) determine what type of function best models the data
C.) find the equation that is the best fit for the data
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- 2. The chief economist for Argus Corporation, a large appliance manufacturer, estimated the firm’s short-run cost function for vacuum cleaners using an average variable cost function of the form AVC = a + bQ + cQ2 where AVC = dollars per vacuum cleaner and Q = number of vacuum cleaners produced each month. Total fixed cost each month is $180,000. The following results were obtained: DEPENDENT VARIABLE: AVC R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 19 0.7360 39.428 0.0001 PARAMETER STANDARDVARIABLE ESTIMATE ERROR T-RATIO P-VALUEINTERCEPT 191.93 54.65 3.512 0.0029 Q - 0.0305 0.00789 23.866 0.0014 Q2 0.0000024…Determine ? such that ?′′(?) = 12? − 1 and 1 is both a critical number and a y- intercept of ?.The following data shows the atmospheric pollutants yi(relative to an EPA standard) at half hour interval xi. Find the equation y=a+bx of the least square line that best fits the data points given by 2,1, 5,2, 7,3, 8,3. Hence predict the atmospheric pollutant at x=6 half hour.
- Accountants at the Tucson firm, Larry Youdelman,CPAs, believed that several traveling executives were submittingunusually high travel vouchers when they returned from businesstrips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regres-sion equation relating expected travel cost to number of days on the road ( x1 ) and distance traveled ( x2 ) in miles:yn = +90.00 + +48.50x1 + +.40x2The coefficient of correlation computed was .68.a) If Donna Battista returns from a 300-mile trip that took herout of town for 5 days, what is the expected amount she shouldclaim as expenses?b) Battista submitted a reimbursement request for $685. Whatshould the accountant do?c) Should any other variables be included? Which ones? Why?Imagine that a professor of psychology has two teaching assistants (TAs) who will help her grade assignments for the duration of the semester. The professor wants to make sure that she and the TAs are well calibrated with one another, so she has all three of them grade the first assignment independently. Because the professor grades every assignment on a curve, she first converts the students’ scores to z-scores for each grader. The following table shows the z-scores for a population of 10 students in her class for each grader. Professor Teaching Assistant #1 Teaching Assistant #2 Student 1 0.70 1.27 1.27 Student 2 0.83 -0.64 -1.55 Student 3 -0.98 0.38 -0.14 Student 4 2.21 0.80 0.92 Student 5 -0.54 -1.34 -1.06 Student 6 0.43 0.10 0.30 Student 7 -1.03 -2.09 -1.50 Student 8 -0.01 0.85 1.14 Student 9 -0.54 0.48 0.57 Student 10 -1.07 0.20 0.04 The professor is going to use the z-scores to calculate the correlation coefficient between her scores…Which of the following is a reason why fixed effect models can't estimate coefficients on variables that do not vary within unit? A, The errors will be homoscedastic. B, The de-meaned variables will not vary. C, We can estimate such a variable with fixed effects. D, Because no fixed effects exists in such a case.
- Here is the number of twins born in select years in thousands of births: Year: 1995 1997 1999 2001 2003 number of Twin births: 96.7 104.1 114.3 121.2 128.7 A) Model the data witha linear function based on the data from 1995 and 1997. Let the input varaible be the number of years after 1995 and the output varaible represent the number of twin births in thousands. Thus two points would be (0, 96.7), (2, 104.1) B) With the function found in part (a), to show what the model predicts will happen in the other years listed (1999, 2001, 2003). How close is the model in those years? C)Use the model to predict how many twin births there will be in the year 2010.The following table gives the millions of metric tons of carbon dioxide emissions in a certain country for selected years from 2010 and projected to 2032. Year 2010 2012 2014 2016 2018 2020 CO2 Emissions 337.5 361.5 395.1 425.8 451.1 496.4 Year 2022 2024 2026 2028 2030 2032 CO2 Emissions 558.2 592.9 628.7 662.1 709.1 742.7 (a) Create a linear function that models these data, with x as the number of years past 2010 and y as the millions of metric tons of carbon dioxide emissions. (Round all numerical values to two decimal places.)y(x) = (b) Find the model's estimate for the 2028 data point. (Round your answer to two decimal places.) million metric tons(c) Find the slope of the linear model. (Round your answer to two decimal places.)Interpret the slope of the linear model. For each year since ---Select--- 2009 2010 2015 2028 2032 , carbon dioxide emissions in the U.S. are expected to change by million metric tons.Non-fulfilment of the zero-mean assumption for the disturbance term leads to the problem of _____. Select one: a. biased intercept and slope b. biased intercept c. none of the above d. biased slope
- The chief economist for Argus Corporation, a large appliance manufacturer, estimated the firm’s short-run cost function for vacuum cleaners using an average variable cost function of the form AVC = a + bQ + cQ2 where AVC = dollars per vacuum cleaner and Q = number of vacuum cleaners produced each month. Total fixed cost each month is $180,000. The following results were obtained: DEPENDENT VARIABLE: AVC R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 19 0.7360 39.428 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 191.93 54.65 3.512 0.0029 Q -0.0305 0.00789 23.866 0.0014 Q2 0.0000024 0.00000098 2.449 0.0262 c) If Argus Corporation produces 8,000 vacuum cleaners per month, what is the Marginal cost?The chief economist for Argus Corporation, a large appliance manufacturer, estimated the firm’s short-run cost function for vacuum cleaners using an average variable cost function of the form AVC = a + bQ + cQ2 where AVC = dollars per vacuum cleaner and Q = number of vacuum cleaners produced each month. Total fixed cost each month is $180,000. The following results were obtained: DEPENDENT VARIABLE: AVC R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 19 0.7360 39.428 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 191.93 54.65 3.512 0.0029 Q -0.0305 0.00789 23.866 0.0014 Q2 0.0000024 0.00000098 2.449 0.0262 f) At what level of output will average variable cost be at a minimum?The chief economist for Argus Corporation, a large appliance manufacturer, estimated the firm’s short-run cost function for vacuum cleaners using an average variable cost function of the form AVC = a + bQ + cQ2 where AVC = dollars per vacuum cleaner and Q = number of vacuum cleaners produced each month. Total fixed cost each month is $180,000. The following results were obtained: DEPENDENT VARIABLE: AVC R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 19 0.7360 39.428 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 191.93 54.65 3.512 0.0029 Q -0.0305 0.00789 23.866 0.0014 Q2 0.0000024 0.00000098 2.449 0.0262 c) If Argus Corporation produces 8,000 vacuum cleaners per month, what is the estimated average variable cost?