HW 5 B_Nguyen_Chapt 9_Fall 2023

Three EV (Electric Vehicle) motor systems are being tested for their efficiency. The following are the data. Motor 1 Motor 2 Motor 3 56 60 58 45 55 54 50 52 53 44 59 50 49 50 52 Using alpha = 0.05, are there any differences between the level of efficiency in the motor systems? *Define the null and alternative hypothesis [ Select ] *Calculate the degrees of freedom, dfoetween , dfwithin, and the dfrotal , respectively [ Select ] *State the decision rule, Feritical [ Select ] *Calculate test statistic, F = [Select] *State result and conclusion [ Select ] > >

First present the equations used in the empirical test of the Heckscher-Ohlin- Vanek (HOV) model explaining all variables, vectors and matrices used. Then present both hypotheses of the HOV model and explain how they relate to the original Heckscher-Ohlin-Samuelson hypothesis.

Suppose the null hypothesis, Ho, is: Darrell has worked 20 hours of overtime this month. What is the Type I error in this scenario? Select the correct answer below: Darrell thinks he has not worked 20 hours of overtime this month when, in fact, he has. Darrell thinks he has not worked 20 hours of overtime this month when, in fact, he has not. O Darrell thinks he has worked 20 hours of overtime this month when, in fact, he has not. Darrell thinks he has worked 20 hours of overtime this month when, in fact, he has. Content attribution FEEDBACK

would u kindly give an example of an economic question then identify variables as well as null and alternative hypothesis (hypotheses like μ > 25)

Why would I use a one-tailed (directional) hypothesis? What are the limitations of using a one-tailed hypothesis?

Suppose you have time series data and estimate the following model y = β0 + β1x1 + ε. When you estimate the model, you find that there are correlated observations (serial correlation). You choose to ignore this issue. What are the consequences? A/ The predictions are biased, but the hypothesis tests are valid. B/ The predictions are not biased, but the hypothesis tests are invalid. C/ Both the predictions and the hypothesis tests are valid. D/ Both the predictions and the hypothesis tests are not valid. Choose the correct answer and briefly explain.

What are the null and alternative hypotheses? Hμ = 100 Hμ > 100 Hμ = 100 Hμ 100 H: a a μ = 140 H_:μ > 140 Η :μ = 140 H_:μ = 140 a What are the null and alternative hypotheses? Ο Ho: μ = 100 H₂: μ> 100 Ho: H = 100 Ha: H100 O Ho: H-140 Ha: > 140 O Ho: H = 140 H₂: μ #140

What are the warnings of using the OLS approach to hypothesis testing? Discuss.

Based on the literature review you finished, now you should develop theory and hypothesis. The number of hypotheses need not be too many, 1-3 hypotheses is enough as long as these hypotheses are TESTABLE. Please think of the data and methods that you will use in order to test the hypotheses that you developed. Theoretical ModelThe theory draws from the model developed by Barro and Lee (1994) which is consistent with the endogenous growth theory. Endogenous growth theory takes into account the sources of technological progress such as human capital and role of government (Romer, 1994). The theory contends that economic growth is related with developments of new ideas, innovation and overall technological change and total factor productivity. Following endogenous growth theory, the concept of “trade openness” in this paper is measured by three variables that take into account of sources of technological change. The three variables that measure trade openness are, trade dependency ratio,…

Consider Scenario A from the previous question. State whether you made a Type I error, a Type II error, or the correct conclusion. Children in your community have on average less than 5.2 books at home, and you reject the hypothesis that they have greater than or equal to 5.2 books.     Children in your community have on average less than 5.2 books at home, and you fail to reject the hypothesis that they have greater than or equal to 5.2 books.     Children in your community have on average greater than or equal to 5.2 books at home, and you reject the hypothesis that they have greater than or equal to 5.2 books.

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Observation: Students on a university campus notice that the freshly squeezed mango juice ferments faster than the freshly made lime juice even though they are made by the same vendor, using the same method of juice extraction, and kept at the same temperature. 1.Write a simple hypothesis, null hypothesis and alternative hypothesis. 2. Suggest a simple step by step method that can be used to test your hypothesis

Finally consider the regression model with an extra covariate: Yi = Bo + B1x1i + B2x2; + €; Let 32=3.13, it's standard error s.e.(B1)=1.12 and assume n=811. Based only on this information, decide if it is useful to include X2i in the regression model. Carefully showing every step of your hypothesis test and explaining your answer. Use signifi- cance level a = .05.

For the given hypothesis test, explain the meaning of a Type I error or a Type II error, as specified. 3) A man is on trial accused of murder in the first degree. The prosecutor presents evidence that he hopes will convince the jury to reject the hypothesis that the man is innocent. This situation can be modeled as a hypothesis test with the following hypotheses: H: The defendant is not guilty. H: The defendant is guilty. a Explain the result of a Type I error (7.1). A) The jury will conclude that the defendant is guilty when in fact he is guilty. B) The jury will fail to reach a decision. ) The jury will conclude that the defendant is not guilty when in fact he is not guilty. D) The jury will conclude that the defendant is guilty when iact he is not guilty. Đ The jury will conclude that the defendant is not guilty when in fact he is guilty.

The following model studies human welfare using the General Social Survey in the US: happy = 0.014 + 0.209regattend + 0.103occattend + 0.027income + 0.009educ +0.003 female where happy is a dummy variable equal to one if a person is happy, and 0 otherwise: regattend is a dummy variable equal to one if a person regularly attends church, and 0 otherwise: occattend is a dummy variable equal to one if a person occasionally attends church, and 0 otherwise; income is family income in tens of thousands: educ is years of schooling: female = 1 if female. = 0 otherwise Interpret the impact of religion on happiness.

Write both a null and research hypothesis for the following variables: study time and academic success exam scores and hours spent sleeping parental support and disciplinary conduct problems

In the hedonic model, what is the alternative hypothesis?   The price impact is 0   There is a positive price impact   There is a negative price impact   The price impact is not equal to 0

The following scatter plot shows hours of study on the X axis and the final exam score on the Y axis for 21 students in an Econometrics 322 class. The round data points are for economics majors; the square points are for non-majors (and yes, non- majors take econometrics). Score hours

Let wage denote hourly wages, educ denote years of education, and define the dummy variable: if educ > 12 D = if educ < 12 i.e. we can think of D as a dummy variable indicating graduation from high school. Suppose we want to test the null hypothesis that the marginal return to education for every year after high school is the same as the marginal return to education for each year before high school (against the alternative that they are different). Which model and test would accomplish this goal? O a. Estimate wage = B1 + B2 educ + ß3 D + e and test Ho : ß3 = B2 against H1 : ß3 # B2. O b. Estimate wage = ß1 + B2educ + ß3 D + e and test Ho : ß3 = 0 against H1 : ß3 # 0. Estimate wage = B1 + B2educ + B3(educ + D) + e and test Ho : ß3 = 62 against H1 : B3 # B2. O d. Estimate wage = B1 + B2educ + B3(D × (educ – 11)) + e and test Ho : ß3 = B2 against H : B3 # B2. c. O e. Estimate wage = Bi + B2educ + ß3(D × (educ – 11)) + e and test Ho : ß3 = 0 against H1 : ß3 + 0.

I have data on the mean price charged for knee replacements (the variable is called, meancharge) at a sample of US hospitals. In STATA, I test whether mean price charge for knee replacement in the population is less than $42.500. The output is shown here. Which of the following statements is false? O. I cannot reject the null hypothesis at the 5% significance level. O. I cannot reject the null hypothesis at the 10% significance level. O. I reject the null hypothesis at the 10% significance level. O. I cannot reject the null hypothesis at the 1% significance level.

Please help me with this question. Thank you.

Consider an equation to explain salaries of CEOS in terms of annual firm sales, return on equity (roe, in percentage form), and return on the firm's stock (ros, in percentage form): log(salary) = Bo + Bilog(sales) + Bzroe + B;ros + u. (i) In terms of the model parameters, state the null hypothesis that, after controlling for sales and roe, ros has no effect on CEO salary. State the alternative that better stock market performance increases a CEO's salary. (ii) Using the data in CEOSAL1, the following equation was obtained by OLS: log (salary) = 4.32 + .280 log(sales) + .0174 roe + .00024 ros (.32) (.035) (.0041) (.00054) n = 209, R2 = .283. By what percentage is salary predicted to increase if ros increases by 50 points? Does ros have a practically large effect on salary? (iii) Test the null hypothesis that ros has no effect on salary against the alternative that ros has a positive effect. Cary out the test at the 10% significance level. (iv) Would you include ros in a final model…

Our null hypothesis is that the true coefficient is zero. In which case would we choose to use a one-sided alternative hypothesis over a two-sided alternative hypothesis? We choose a one sided alternative hypothesis when we have a large sample size. We choose a one sided alternative hypothesis when we specify a low (0.01) significance level. It does not matter what type of alternative hypothesis we specify. Choose a one sided alternative hypothesis when the theory and literature suggests either that the true coefficient should be greater than zero or that the true coefficient should be less than zero.

Give step by step answer with final solution Don't use AI I will downvote

Please solve questions 15, 16 and 17.  The multivariate demand function below will be needed for questions 12-18.   Setting: Grapple, Inc. is a leading seller of laptop personal computers.  However, they want to become a leading tablet seller, too.  Your marketing department, aided by your economics staff, has estimated a function to help you in the quest for market leader in tablets.  The variables are defined after the function. Qg = 10000 - 25Pg + 20Ph + 30Pr - 15dv - 35Psc - 10Pmm + 0.05Ag + 0.03A -25C + 0.1Y                Qg = the number of Grapple tablet computers demanded per week.   Pg = the price of each new Grapple tablet (in $).   Ph = the price of each Hewpaq tablet (in $).   Pr = the price of each Ronova tablet.   Pdv = the price to equip a tablet with Holographic digital video (in $, this is an upgrade option that enables three-dimensional graphics on a tablet.  Two-dimensional graphics is standard equipment).   Psc = the price of various screen sizes (in $, a 8 inch is…

How is the null hypothesis for a correlation different than a null hypothesis for a t-test?

please help me with this asap thanks.

3) A type II error:  A. is the error you make when choosing type II or type I.  B. is typically smaller than the type I error.  C. is the error you make when not rejecting the null hypothesis when it is false.  D. cannot be calculated when the alternative hypothesis contains an "=".

If a police officer wants to find whether the average speed of motorists a highway with speed limit of 55 , the null hypothesis is 55 . true false  justify it

Consider the following Stata output for the model of house prices: lhprice=β0+β1bdrms+β2llotsize+β3lsqrft+u estimated on a random sample of 86 houses. You may assume the Gauss Markov Assumptions hold.  The variables are defined as: lhprice = the natural log of the house price bedrms = the number of bedrooms llotsize = the natural log of the land or lot size lsqrft = the natural log of the floor space of the house in square feet. Source SS df MS Model Residual 4.65621742 2.09289629 3 82 1.55207247 0.025523126 Total 6.74911372 85 0.079401338   lprice  coef. std. err. t P > |t| [95% Conf. Interval] bdrms  0.0581214       -0.0055282 0.121771 llotsize  0.1494716       0.0616548 0.2372884 lsqrft  0.636171       0.421989 0.850353 _cons -0.7083136       -2.221521 0.8048935   Number of obs = 86 F (3, 82) = 60.81 Prob > F = 0.0000 R-squared = 0.6899 Adj R-squared = 0.6786 Root MSE = 0.15976 Does…

When defining the hypothesis, we present…   a.   None of the responses   b.   The null hypothesis only   c.   The alternative hypothesis only   d.   The null and alternative hypotheses