what about learning and fatigue. Draw a graph of the mean as rt a function of trial since the beginning of the run

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(Please use tidyverse. Also, this is an introduction course so please don’t use complex codes and formulas so I can learn it better, thank you. Deadline is today, October 31st before 11pm. Also please give answers in word/pdf because I will need to add more information to the assignment afterwards. ```{r,message=F,warning=F} library('tidyverse') link<-"https://raw.githubusercontent.com/PerceptionCognitionLab/data0/master/lexDec-dist5/ld5.all" dat<-read_table(url(link),col_names=FALSE) colnames(dat)<-c("sub","block","trial","stim","resp","rt","err") dat$rt<-as.numeric(dat$rt) dat$block<-as.numeric(dat$block) dat$trial<-as.numeric(dat$trial) dat$sub<-as.numeric(dat$sub) ``` 1. Let's look at `stim`. `stim` is which number was presented. How many levels are there? What are they? What is the mapping? 2. How many trials total (how many rows in the data)? How many people total? How many trials per person? How many trials per person per digit? 3. - **Quality-Control Check 1**: Do all people have the same number of trials per stimulus? Are there "missing" trials? - **Quality-Control Check 2**: If a response is legitimate, then it should not be too slow, say more than 2 seconds, or too fast, say less than 200 ms. Are all trials within this window? To answer this question, report the fastest and slowest response time. 4. Compute the error rate for each participant. 5. ```{r} dat$totTrial <- dat$block*60+dat$trial+1 ``` How does this code work? How big is `dat` now? Confirm that for each participant, `dat$totTrial` runs from 1 to 360. 6. Now, let's plot the response times for Subject 34 as a function of total number of trials. 7. Make similar plots for Subjects 43 (next most error prone) and 3. 8. Add additional filter statements to exclude trials with times less than 200 ms and greater than 2 seconds. 9. What about learning and fatigue. Draw a graph of the mean RT as a function of trial since the beginning of the run. 10. Write the full cleaning pipe. We will exclude data from Participant 43 and Participant 34, all errors, all responses faster than 200 ms or slower than 2000 ms, the first 20 trials for each participant, and the first trial of a block.

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