hello, please follow each and every question. use simpler codes and mention any packages used for each problem. The homework assignment is filed under Assignment 11 and you will need to use BIG5 and codebook files to answer the questions. Be sure that each code can run through Rstudio with no problems. Also please put the answers inside the file, Assignment 11. I attached all the files needed.
## Run the following to create your dataset: name <- c("bo",="" "luke",="" "jesse",="" "cooter",="" "daisy")="" i1=""><- c(1,2,3,4,5)="" i2=""><- c(2,5,1,5,4)="" i3=""><- c(3,2,na,5,1)="" i4=""><- c(2,3,6,5,4)="" temp=""><- as.data.frame(cbind(i1,i2,i3,i4))="" data=""><- cbind(name,temp) ## 1. what's the correlation between i1 and i2? ## 2. create a raw scale score for each person (across the 4 items) that represents the average item response. ## place this at the end of your "data" object (be sure to make sure that jesse has a valid scale score) ## 3. compute transformed standard scores (e.g., derived from z-scores) with a mean of 10 ## and standard deviation of 3. place these scores at the end of your "data" object. ## 4. what's the alpha for your 4-item scale? ## alpha: ## 5. what's the corrected item-total correlation for item 3? ## corrected item-total correlation item 3: ## 6. go to this website and download the data and codesheet for the big5 onto your local machine: ## https://openpsychometrics.org/_rawdata/ ## ...you can also access these files via canvas: the codesheet is "codebook.txt" and the data in .csv format is "big5.csv" ## do you believe this data is in raw form or has already been recoded - why? ## 7. using: 1) the codebook, 2) your knowledge of the five factor model, and 3) corrected item total correlations, develop a scoring key for this data (indicate which items you are suggesting should be recoded): ## 8. apply your scoring key and create standardized scale scores for each person in the dataset. for extraversion, set the standardized scale score mean to 10 and standard deviation to 1. for neuroticism, set the mean to 15 and sd to 5. for agreeableness, set the mean to 20 and sd to 10, for conscientiousness, set the mean to 25 annd sd to 15, for openness, set the mean to 30 and sd to 20. make sure to append these scale scores within your dataframe. ## 9. plot your 5 standardized scale scores within the same plotting space (e.g., just one picture but with 5 frequency distributions). ## 10. if a new person were to take this inventory and score a "20" on neuroticism (using your standardized scale score), what would their percentile rank be? ########################################################################## ######################## have a good summer! ############################# ########################################################################## cbind(name,temp)="" ##="" 1.="" what's="" the="" correlation="" between="" i1="" and="" i2?="" ##="" 2.="" create="" a="" raw="" scale="" score="" for="" each="" person="" (across="" the="" 4="" items)="" that="" represents="" the="" average="" item="" response.="" ##="" place="" this="" at="" the="" end="" of="" your="" "data"="" object="" (be="" sure="" to="" make="" sure="" that="" jesse="" has="" a="" valid="" scale="" score)="" ##="" 3.="" compute="" transformed="" standard="" scores="" (e.g.,="" derived="" from="" z-scores)="" with="" a="" mean="" of="" 10="" ##="" and="" standard="" deviation="" of="" 3.="" place="" these="" scores="" at="" the="" end="" of="" your="" "data"="" object.="" ##="" 4.="" what's="" the="" alpha="" for="" your="" 4-item="" scale?="" ##="" alpha:="" ##="" 5.="" what's="" the="" corrected="" item-total="" correlation="" for="" item="" 3?="" ##="" corrected="" item-total="" correlation="" item="" 3:="" ##="" 6.="" go="" to="" this="" website="" and="" download="" the="" data="" and="" codesheet="" for="" the="" big5="" onto="" your="" local="" machine:="" ##="" https://openpsychometrics.org/_rawdata/="" ##="" ...you="" can="" also="" access="" these="" files="" via="" canvas:="" the="" codesheet="" is="" "codebook.txt"="" and="" the="" data="" in="" .csv="" format="" is="" "big5.csv"="" ##="" do="" you="" believe="" this="" data="" is="" in="" raw="" form="" or="" has="" already="" been="" recoded="" -="" why?="" ##="" 7.="" using:="" 1)="" the="" codebook,="" 2)="" your="" knowledge="" of="" the="" five="" factor="" model,="" and="" 3)="" corrected="" item="" total="" correlations,="" develop="" a="" scoring="" key="" for="" this="" data="" (indicate="" which="" items="" you="" are="" suggesting="" should="" be="" recoded):="" ##="" 8.="" apply="" your="" scoring="" key="" and="" create="" standardized="" scale="" scores="" for="" each="" person="" in="" the="" dataset.="" for="" extraversion,="" set="" the="" standardized="" scale="" score="" mean="" to="" 10="" and="" standard="" deviation="" to="" 1.="" for="" neuroticism,="" set="" the="" mean="" to="" 15="" and="" sd="" to="" 5.="" for="" agreeableness,="" set="" the="" mean="" to="" 20="" and="" sd="" to="" 10,="" for="" conscientiousness,="" set="" the="" mean="" to="" 25="" annd="" sd="" to="" 15,="" for="" openness,="" set="" the="" mean="" to="" 30="" and="" sd="" to="" 20.="" make="" sure="" to="" append="" these="" scale="" scores="" within="" your="" dataframe.="" ##="" 9.="" plot="" your="" 5="" standardized="" scale="" scores="" within="" the="" same="" plotting="" space="" (e.g.,="" just="" one="" picture="" but="" with="" 5="" frequency="" distributions).="" ##="" 10.="" if="" a="" new="" person="" were="" to="" take="" this="" inventory="" and="" score="" a="" "20"="" on="" neuroticism="" (using="" your="" standardized="" scale="" score),="" what="" would="" their="" percentile="" rank="" be?="" ##########################################################################="" ########################="" have="" a="" good="" summer!="" #############################="">