Derive the two expressions for the IS and LM equilibrium relationships respectively. Sketch a graph of the two relationships. Consider a closed economy where the goods and money markets are described by the following relationships:C = 500+ 0.8(Y – T)-I = 500 10rMP= 0.1Y - 35rG = 800T = 200M = 1000P = 2Where C is planned consumption, I is planned investment spending, T is government tax revenues, G isgovernment purchases, M is the money supply, P is the price level and r is the interest rate.

IS explain investment savings and LM equilibrium explain liquidity preference money. The graphical…

Answered: Derive the two expressions for the IS…

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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The following output from R presents the results from computing a linear model. In our data example we are interested to study the relationship between TV budget and sales This R output is for a simple data set that contains, in thousands of dollars, TV budget for 200 different markets along with the Sales, in thousands of units, for each market. summary (model1) ## ## Call: ## Lm (formula = Sales TV, data = train) ## ## Residuals: ## Min 10 Median 30 Max ## -8.5816 -1.7845 -0.2533 2.1715 6.9345 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 6.764098 ## TV 0.607592 11.13 <2e-16 ***k 0.050284 0.003463 14.52 <2e-16 *** ## --- O '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## Signif. codes: #2# ## Residual standard error: 3.204 on 120 degrees of freedom ## Multiple R-squared: 0.6373, Adjusted R-squared: 0.6342 ## F-statistic: 210.8 on 1 and 120 DF, p-value: < 2.2e-16 confint (model1) ## 2.5 % 97.5 % ## (Intercept) 5.56110868 7.96708701 ## TV 0.04342678…
Match each scatterplot to the statement that best describes it. : 12 12 10 10- 2 6- 4 4 2- 2- 10 12 6. 12 (a) (b) 12 12 10- 10- > 6F > 6- 4 2 10 12 10 12 (c) The relationship between x and y is approximately linear. The relationship between x and y is nonlinear. iii. There isn't much of any relationship between x and y. iv. The relationship between x and y is approximately linear, except for an outlier. i. ii.
The teenage birthrate in the United States has declined since 1995 as shown to the right. Let B be the American teenage birthrate (number of births per 1000 women ages 15-19) at t years since 1995. a. Find an equation of a linear model to describe the data. b. Predict the teenage birthrate in 2020. Then predict the number of births to women in 2020, assuming that there will be 11,007,000 women ages 15-19 in that year. c. Predict in which years the birthrate will be less than 11.4 births per 1000 women ages 15-19. Birthrate (number of births per 1000 women ages 15-19) Year 1995 56.0 2000 47.7 2005 40.5 2010 34.3 2015 24.2 a. Using the points (0,56.0) and (10,40.5), the equation of linear model is B = (Use integers or decimals for any numbers in the expression.) Enter your answer in the answer box and then click Check Answer.
Consider the web model with the supply and demand equations given by Find the intertemporal equilibrium price, and determine the equilibrium rate and its stability.
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Part A: You are calibrating a temperature sensor that you believe will have a linear input/output relationship. You collect the three data points below: Temperature (C) 0 50 100 Output Voltage (V) 1.2 1.9 3.2 You wish to find output Voltage as a function of input Temperature (i.e., the calibration curve), and assume a linear relationship of the form: V = a₁T + ao Using the method and equations we discussed in class, find the coefficients a, and a for the best fit regression line.
The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995. 220- 210- 200- 190- 180- 170- 160- 150 140- 130 120- 110- 100- Year 0 3 90+ 801 6 9 12 15 Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is S(t) = 9.44t + 84.182. Retail Sales 85.851 108.426 141.781 169.256 202.297 222.266 3 6 9 12
20. A weather balloon is released from a tower. The graph shows the balloon's height above the ground, y, after x seconds. Weather Balloon 100 90 80 70 60 50 40 30 20 10 10 20 30 40 Time (seconds) 50 Which equation best represents the relationship between x and y? TEKS 6.6C F. у %3D х + 25 G. X %3D у + 25 Н. у %3D 25х J. x = 25y Height (feet)
3. Travelers who have no intention of showing up often fail to cancel their hotel reservations in a timely manner. These travelers are known, in the parlance of the hospitality trade, as "no-shows". To protect against no-shows and late cancellations, hotels invariably overbook rooms. A recent study examined the problems of over-booking rooms in the hotel industry. The following data, extracted from the study represent the daily numbers of late cancellations and no-shows for a random sample of 10 days at a hotel: 18, 16, 16, 16, 14, 18, 16, 18, 14, 19. c) Count the number of measurements that actually fall within the interval(-28, +2s) and express the interval count as a percentage of total number of measurements. at least 75% 100% 68% 95%
Hotel Managers' Personalities. Successful hotel managers must have personality characteristics often thought of as feminine (such as "compassionate") as well as those often thought of as masculine (such as "forceful"). The Bern Sex-Role Inventory (BSRI) is a personality test that gives separate ratings for female and male stereotypes, both on a scale of 1 to 7. A sample of 148 male general managers of three-star and four-star hotels had mean BSRI femininity score y = 5.29 The mean score for the general male population is μ = 5.19. Do hotel managers, on the average, differ significantly in femininity score from men in general? Assume that the standard deviation of scores in the population of all male hotel managers is the same as the σ = 0.78 for the adult male population. (a) State null and alternative hypotheses in terms of the mean femininity score μ for male hotel managers. (b) Find the z test statistic. (c) What is the P-value for your z? What do you conclude about male hotel…
The data in the following table show five students' reading test scores and final exam grades in a history class. Reading Test Score, x 8.5 9.4 10.0 11.4 12.0 History Final Exam Grade, y 66 68 78 87 92 (a) Use the points (8.5, 66) and (10.0, 78) to find a linear model that will predict a student's final exam grade, y, given his or her reading test score, x. y= (b) Use your linear model to estimate a student's final exam grade in the history class given that the student's reading test score was 10.5.

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