24. A manufacturing plant output model is Q = ß₁+ ß2MGTEFF + ß3CAP + ß4LAB + e,where Q is the output in a particular manufacturing plant, MGTEFF is a managerialefficiency index, CAP is capital stock input index and LAB is labor input index.Measuring MGTEFF is difficult. Suppose Q B₁+ B₂EXPER+ ß3CAP + ß4LAB + ewhere EXPER is the plant manager's experience, measured in years is proposed. Whymight we worry that EXPER is endogenous?A. Manager's experience may have measurement errorsB. Manager's experience maybe correlated with omitted variables.C. Plant output and manager's experience maybe jointly determined.D. All the above.25. Ordinary least squares method assumes time series data are stationary. Which of thefollowing depicts a stationary time series?1816-14-12-10-8-6-wymgmgmgmypergunjungmp-rpiqunjungtung84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16(a) Real gross domestic product (GDP), Strillion (quarterly)1612-8-4-0--455 60 65در استان ها باINF70 75 80 85 90 95(c) Inflation, percent (monthly)A. Real GDPB. Change in real GDPC. InflationD. Change in inflation00 05 10 15стриальную-0.4mmvepupupuya84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16(b) Change in GDP (quarterly)0.30.2-0.1-0.0--0.1--0.2--0.3-55 60 6570 75 80 85 90 95 00(d) Change in inflation (monthly)וווווווווד05 10 15

24. A manufacturing plant output model is given by: Q=β1+β2MGTEFF+β3CAP+β4LAB+e Where: Q=…

Answered: A manufacturing plant output model is Q…

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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People gain weight when they take in more energy from food than they expend. Researchers wanted to investigate the link between obesity and energy spent on daily activity. Choose 20 healthy volunteers who don't exercise. Deliberately choose 10 who are lean and 10 who are mildly obese but still healthy. Attach sensors that monitor the subjects' every move for 10 days. The table below presents data on the time (in minutes per day) that the subjects spent standing or walking, sitting, and lying down. Is there a significant difference between the mean times the two groups spend lying down? Let ?1 be the mean time spent lying down by the lean group, and ?2 be the mean time for the obese group. Time (minutes per day) spent in three different postures by leanand obese subjects Group Subject Stand/Walk Sit Lie Lean 1 509.100 366.300 554.500 Lean 2 603.925 374.512 452.650 Lean 3 322.212 580.138 533.362 Lean 4 581.644 362.144 489.269 Lean 5…
You were asked to help with an analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers’ AGE at birth (continuous variable in years), mothers’ current HOUSING status (“own” and “not-own”; “own” is the reference group), and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”; “Manhattan” is the reference group). Write down the population model that estimates the effect of mother’s AGE on BW while adjusting for mother’s current HOUSING status. If you use dummy or binary variables, specify what they mean. Write down the population model that estimates the effect of mother’s AGE on BW while adjusting for mother’s current HOUSING status and BOROUGH. If you use dummy or binary variables, specify what they mean. Write down the population model that estimates the effect of mother’s AGE…
In addition to therapy, anti-depressant drugs are used in the treatment of depression. The data below are from a study comparing two anti-depressant drugs. A baseline measurement for symptomatic behavior for depression is taken. After treatment with medication, another measurement taken. The data given in the table is for improvement which is for the reduction in symptomatic behavior.
58. Fit a straight line trend by least squares method and tabulate the trend Pvalues from the following figures of production of a cement factory : Year Production ('000 tonnes) : 2008 77 2009 88 2010 94 2011 2013 2012 91 2014 90 85 98
Suppose we obtain data on prices of big-screen televisions and estimate the following model: In(Price) = 4.06 + 0.06 * Size +0.23 * Wide + 0.34 * Plasma + 0.21 * LCD+0.09 * Memory where the dependent variable has been transformed, Size is the screen size measured in inches, Wide is a dummy variable equal to one if the television is a widescreen, Plasma is a dummy variable equal to one if the television is a Plasma screen, LCD is equal to one if the television is an LCD screen, and Memory is a dummy variable equal to one if the television has any memory card slots. What is the estimated price of a 42" Widescreen Plasma television with 2 memory card slots? Select one: O a. 7.24 O b. 7.33 1525.38 O d. 1394.09 • e 1881.83 Clear my choice
Fiske Corporation manufactures a popular regional brand of kitchen utensils. The design and variety has been fairly constant over the last three years. The managers at Fiske are planning for some changes in the product line next year, but first they want to understand better the relation between activity and factory costs as experienced with the current products. Discussions with the plant supervisor suggest that overhead seems to vary with labor-hours, machine-hours, or both. The following data were collected from last three year's operations: Quarter Machine-Hours 18,850 4 5 6 7 8 9 10 11 12 18,590 17,480 19,240 21,280 19,630 19,240 18,850 18,460 20,670 17,550 18,460 Labor-Hours 15,605 15,484 16,727 15,990 17,508 17,376 15,297 14,373 16,001 17,002 14,285 17,651 Factory costs $ 3,395,671 3,425,836 3,617,844 3,573,940 3,812,984 3,778,012 3,532,426 3,369,802 3,513, 187 3,731,434 3,325,615 3,724,486 Required: Prepare a scatter graph based on the factory cost and labor-hour data. Note: 1.…
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that assumes the effect of mother’s AGE at birth on infant weight BW is DIFFERENT for different levels of maternal smoking status (MSS) when adjusted for BOROUGH variable. Specify the name of each predictor in the model and/or what it means. Make sure that it is clear what each predictor means.
please answer correctly:
Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin, - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team===== "Brooklyn Nets" . Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1459.95122 1 80 190.65061 None of the above 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 MS t Number of obs F(1, 80) Prob > F R-squared O The Nets lost more games than they won in 2014 P>|t| 2.77 0.007 -2.42 0.018 Adj R-squared = Root…
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1.Write down the population model that estimates BW based on variables AGE and BOROUGH(with the dummy variables). Make sure that it is clear what each predictor means. 2.How many parallel lines are computed by model from population model you created above? 3.Write down the population model that estimates BW based on variables AGE, MSS(with their dummy variables) and BOROUGH(with their dummy variables). Also write down the number of parrallel lines.…
The relationship between United States unemployment and inflation rates during the Covid-19 pandemic. Background The covid-19 pandemic has led to higher unemployment rates in the United States than normal because many people were laid off jobs in response to the pandemic (Al-Fadly, 2020). It is important to analyze how such as sharp increase in unemployment affected inflation in relation to how unemployment have traditionally affected inflation. The overall relationship between unemployment and inflation has traditionally been an inverse one. It is argued that when unemployment rates are higher, the number of individuals who are looking for jobs usually becomes higher than the number of job positions that are available (Putnam & Azzarello, 2015). In such a situation, employers tend to pay lower wages because there is abundance of workers which naturally leads to a lower wage inflation. This study will examine the relationship between unemployment rates and inflation rate during…
Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin; - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team==== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1 80 Coef. Std. Err. MS 81 206.320988 8.439024 3.049595 -5.219512 2.156389 1459.95122 190.65061 t Number of obs F (1, 80) Prob > F R-squared. Adj R-squared = Root MSE P>|t| 2.77 0.007 -2.42 0.018 82 7.66 0.0070 0.0874 0.0760 13.808 [95% Conf. Interval]…

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