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STAT 3503 Regression Analysis

创建日期：2024-04-18 15:52:38

所属分类：统计学statistics

标签： STAT 3503

Regression Analysis

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STAT 3503 Regression Analysis

Assignment #2 Consider i.i.d observations and the usual regression model with

All plots should have titles Level 1 questions, easy or direct from the book: 1. (2points)

Set up the matrix and vector assuming that n = 4 2. (4points) Show that an equivalent

way to write the above regression model is Level 2 questions, challenging if its been a

while you have done this. 3. (20points) A. (1point) Obtain the Trade Data of monthly export of

grains from Statistics Canada’s Open Government. Clean and organize your data as you observe on the

website provided. Make a scatter plot of the year of export (year) against the total exports in tonnes (total)

B. (3points) Remake the plot in part A but first subset the data so that you are only considering  

two commodities: “Barley”, “Oats”. Make sure you color the points with the type of commodity.

Include in your plot one single regression line for this subset of the dataset, add a second regression

line for this subset of data, but make sure you force the line to have a zero intercept. C. (6points, 3points for each model )

Write down the mathematical formulae for the two regression models included in your plot in B and

provide clearly how you will fit these two models in R. Make a 95% confidence interval for the slope and intercept for the first model Make a 95% confidence interval for the slope for the second model Finally put your answer into a complete sentence for each model. D. (5points each: 1point hypotheses, 3points appropriate number to do the problem mathematically by hand, 1point conclusion) Test the hypothesis that total export of Barley and Oats are increasing by 5 tonnes. Test the hypothesis that when there is no fiscal year, there are no exports of Barley and Oats. Y1,…,Yn Yi = β0 + Xi1β1 + Xi2β2 + εi εi ∼ N(0,σ2) X β ̂Yi = Y¯ + β1(Xi1 − X¯1) + β2(Xi2 − X¯2) STAT 3503 Regression Analysis 4. (16 points) Modify your data from part B by adding a dummy variable with Barley ==1 and Oats==0. A. (2points) Write down the appropriate regression model for this new dataset. State clearly the intercepts for commodities Barley and Oats. B. (2points) Make a 95% confidence interval for the intercept of Barley C. (2points) Make a 95% confidence interval for the intercept of Oats D. (3points: 1point hypotheses, 1 point appropriate numbers to do the problem mathematical by hand, 1 point conclusion) Test the hypothesis that total export of Barley is greater than the total export for Oats. E.(7points) Consider the data for only Barley using your data in part D. Make a 90% Confidence Interval for the mean observation for year 2019.

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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 EMESTER1 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