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经济代考 Economic Data代写

2022-01-02 09:44 星期日 所属: 经济学代写 浏览:586

经济代考

ECON 333: Statistical Analysis of Economic Data (Spring, 2020)

经济代考 We will focus on linear regression, which is by far the most common method for analyzing the relationship between two or more variables.

Lectures: Tuesday 8:30AM -10:20AM, Thursday 8:30AM – 9:20AM, C9000.

Office hours: Tuesday 2:40PM – 4:20PM, WMC 3627.

What to expect in this course:

This course will introduce you to the statistical analysis of economic data, AKA econometrics. We will focus on linear regression, which is by far the most common method for analyzing the relationship between two or more variables. The main things you will learn in this class are how to apply regression methods to economic data and how to interpret the results of econometric analysis. You will also get some experience using statistical software and establish a foundation for further econometric study.  经济代考

Course materials (lecture notes, assignments, assigned readings, announcements, etc.) will be delivered via Canvas. It is your responsibility to check it regularly.

Readings:

The text for the course is Jeffrey M. Wooldridge (2019) “Introductory Econometrics: A Modern Approach” (7e). Assigned readings and an approximate schedule will be posted on canvas and updated as the semester progresses. You’re expected to do the readings before the accompanying lecture.

经济代考
经济代考

Assignments:   经济代考

There will be regular graded assignments consisting of both exam-type questions and computer exercises. You are expected to work independently on the assignments. Cheating of any kind will result in penalties based on the full extent of the relevant policy.

The computer exercises will get you doing some real econometric analysis using the R software package. R is open source, so you can also freely download a copy for your own use here: https://www.r-project.org. I encourage you familiarize yourself with R before the start of the semester. You’ll find a brief introduction here: https://www.r-econometrics.com/rbasicsintro/.

If you would prefer something book-length, I recommend R for Data Science by Grolemund and Wickham. There’s a free online version at https://r4ds.had.co.nz, or you can buy a hardcopy: https://www.amazon.ca/dp/1491910399/ref=cm_sw_em_r_mt_dp_U_4ATBDbWMGVEVY

Lab:   经济代考

R is installed in all drop-in labs on campus. We will also have dedicated open lab hours in WMC 2506. There will be a TA in the open lab from 3:30-6:30 pm on Wednesday during the weeks that an R assignment is due. Outside those hours, I encourage you to use any of the drop-in labs on campus.

Tutorials   经济代考

The tutorials are primarily a venue for you to ask questions. In addition, they will be a venue to discuss the assignments, review for the midterm/final, and discuss the lectures and readings.

Grading:

Your grade in this class will be based on tutorial participation (10%), assignments (25%), one midterm (30%, tentatively scheduled for Feb. 25), and a cumulative final exam (35%, Apr. 17).

经济代考
经济代考

 

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