You will use both script and data files (10th week, 2nd session files under RStudio in Canvas: 102_210_data_file & 102_210_script_file) for this assignment.
File 1: PDF file, FirstName_LastName_LA#2.pdf
File 2: RScript, FirstName_LastName_LA#2.r
File 3: RData, FirstName_LastName_LA#2.rdata (This file will be named by your script file).
Together with a pdf copy of this file including your answers, you will send your final R script and your RData file. You will update your RData file name as shown in the script by simply following the steps in the script. Also, make sure that you update your Rscript and PDF file names manually.
Do not forget to save any changes/updates you made to your codes in RScript file.
Note that I will cut points for improper assignment submissions (check the grading rubric). On the other hand, I will give additional 5 points when an assignment is submitted in a very clear and proper format.
Note: Round up numbers to two decimals places (4.732 => 4.73, 4.735 => 4.74) in your answers.
1. Simply copy and paste the results that you see in Console after running the command in line 102: tail(zdf)
2. Interpret the results that you see in Console after you run the command in line 104:
zdf[which(rownames(zdf) %in% c("SPA","SWI","URU","USA")),
c("Happy","HappyZ")]
3. Why we used the command in line 112: zdf[which(rownames(zdf)=="USA"),c("Happy","HappyZ")]
4. Report the values of (1) Happy variable and (2) z-score for Belgium (BEL). Note that you can use the command in the previous question as a reference.
5. Describe what x and z, as seen in the picture below, mean in your own words.
6. Copy and paste the normal shape graph where the shaded area is greater than 1.0479:
(tigerstats::pnormGC(z,region="above",mean=0,sd=1,graph=TRUE))
7. Copy and paste the normal shape graph where the shaded area is between 0 and 1.0479:
(tigerstats::pnormGC(c(0,z),region="between",mean=0,sd=1,graph=TRUE))
8. Copy and paste the normal shape graph where the probability is between South Africa (SOU) and Switzerland (SWI)?
tigerstats::pnormGC(c(z1,z2),region="between",mean=0,sd=1,graph=TRUE)
9. What is the probability of the covered area for the question above?
abs(0.5-pnorm(abs(z1),mean=0,sd=1,lower.tail=FALSE)) + (0.5-pnorm(abs(z2),mean=0,sd=1,lower.tail=FALSE))
10. What z score cuts off a normal distribution such that 2.5% of scores are above that +z score in a large population and 2.5% of the scores are below -z?
(Note that you can even answer this question without using RStudio, but it is recommended to understand the steps in the script.)
11. The codes in the picture below show how to calculate the standard error of the Happy variable by hand using data from the simulation example (Central Limit Theorem part) in RStudio.
Considering the codes and the steps above, how would you calculate the standard error of Health variable given the example above? Type your codes into the space below:
12. Considering the simulation and the codes that you created for the question above, report the standard error for the Health variable?
Questions 13, 14, 15: The codes in the picture below show calculating confidence intervals by hand for Happy variable.
13. Given the picture above, explain Part 1 in your own words:
14. Given the picture above, explain Part 2 in your own words:
15. Given the picture above, explain Part 3 in your own words:
16. Report upper and lower confidence interval limits for the Happy variable at the 95% confidence level?
(ciDesc <- DescTools::MeanCI(df$Happy, method="classic", conf.level=0.95, na.rm=T))
17. Report upper and lower confidence interval limits for the Happy variable at the 99% confidence level? (Note you can use the command for the Happy variable as a reference.)
18. Report upper and lower confidence interval limits for the Health variable at 99% confidence level?
19. Submit RScript as a separate file as mentioned in the instructions.
20. Submit RData as a separate file as mentioned in the instructions.
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