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EMET8002 Linear regressions
创建日期：2024-05-14 18:13:09
所属分类：统计学statistics
标签： EMET8002
Linear regressions

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EMET8002 


Quiz 2 is worth 20% of your final mark. There are three questions and you have to
answer all three of them. You can work on these questions in your own time and you
need to submit your answers through the Turnitin link on Wattle any time before the
due date.

Question 1 - Approximately 600 words [7 marks]
This question does not require you to undertake any analysis yourself. Rather, you are
being asked to critique an existing paper on “The impact of COVID-19 on racial inequality in
business earnings” by Fairlie 


Answer the following questions in your own words.
1a) What are the research questions and what data is used to test those questions? Include a
discussion of the strengths and weaknesses of the data used in this paper. [2 marks]
1b) What are the main data analysis techniques used to test those research questions (from
part a)? Describe at least one of those techniques in detail. [3 marks]
1c) How could the analysis be extended using a different model or technique? [2 marks]

Question 2 [6 marks]

These questions are based on the content from our guest lectures in Weeks 9 and 11.
Choose one best answer for each question.

2.1 The bias-variance trade off does not apply in machine learning problems when –

a- The machine learning models used are complex
b- Data has missing values
c- Linear regressions are used
d- None of the above
2

2.2 Cross-validation can be used to compare different machine learning models.

a- True
b- False

2.3 One advantage of using a decision tree over linear regression model is that a decision tree
model will always produce more accurate predictions than a linear regression model.

a- True
b- False

2.4 Why was the expansion of the Medicaid program in Oregon so exciting to economists?

a- It provided affordable health care to all vulnerable individuals in Oregon.
b- It provided a large sample size so that economists could use quantile regressions to
address endogeneity.
c- It enabled causal inference because it was a natural experiment based on lottery
drawings.
d- It was a large-scale program that successfully reduced emergency department visits in
Oregon.


2.5 Difference-in-difference methods are a special case of random-effect models.

a- True
b- False

2.6 RCTs cannot be used to establish causal inference.

a- True
b- False


Question 3 – Approximately 600 words [7 marks]

This question requires you to undertake your own analysis. For one of the datasets used
in the computer labs this year:
3a) Identify a dependent variable that could be estimated by a binary, ordered or multinomial
logit model. Which of these models would you recommend for estimating this variable?
Justify why you would choose this model over the other. [2 marks]
3
3b) Describe an economic research question that can be analysed with the model and the
dependent variable that you chose in part (a). State your null and alternative hypotheses.
Remember to back up your research question with existing literature and/or theory (2-3
references). [2 marks]
3c) Estimate a model with no more than five independent variables to test your research
question from part (b). Present your findings in a Table and interpret the sign and the
statistical significance of the coefficients. Do you find evidence to support your research
hypothesis? Explain. [3 marks]
Include your Stata code (log file) in your assignment submission.
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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