For each student (ie. `sid`), find the average marks of the all courses taken. You are asked to have one average value for each student in the result. df2 % XXXX(sid) %>% XXXX(ave_grade = mean(grade, na.rm = TRUE)) Please fill in the blanks below. df2 % [Fill in the blank] (sid) %>% [Fill in the blank] (ave_grade = mean(grade, na.rm = TRUE))

To tackle this problem, I’ll walk through what each blank should do in the dplyr chain and how they work together. Option analysis for the first blank: - group_by: This function is used to group the data by one or more variables. Since the task is to compute an average per student, grouping by sid is the correct approach to create subsets of each student’s records before summarising. Option analysis for the second blank: - summarise (American English spelling) and summarise: Both spellings are accepted in dplyr and refer to the same function that reduces each group to a single row by computing summary statistics. In this case, we want ave_grade = mean(grade, na.rm = TRUE), which produces the per-student average Grade while ignoring missing values. - Could there be an alternative spelling (summarize) instead of summarise? Yes, summarize is the same function with the American spelling; either will work in most environments depending on the locale and version of dplyr. The important part is that it computes a per-group summary and assigns it to ave_grade. Putting it together: - When you use group_by(sid) followed by summarise(ave_grade = mean(grade, na.rm = TRUE)), you group the data by each student id and then compute the average grade within each group, yielding one average per student as required. Common pitfalls and clarifications: - If you omit group_by, summarise would still return a single row for the entire dataset instead of per-student averages, which is not what we want. - If you forget na.rm = TRUE, missing grades would propagate into the mean calculation, potentially producing NA results for some groups. - The choice between summarise and summarize does not affect the result; it’s simply a spelling variant. In summary, the blanks should be filled with group_by for the first blank and either summarise or summarize for the second blank to achieve one average per student.

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COMM_V 205 101 102 103 2025W1 R Review Quiz

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For each student (ie. `sid`), find the average marks of the all courses taken. You are asked to have one average value for each student in the result. df2 <- student %>% XXXX(sid) %>% XXXX(ave_grade = mean(grade, na.rm = TRUE)) Please fill in the blanks below. df2 <- student %>% [Fill in the blank] (sid) %>% [Fill in the blank] (ave_grade = mean(grade, na.rm = TRUE))

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To tackle this problem, I’ll walk through what each blank should do in the dplyr chain and how they work together. Option analysis for the first blank: - group_by: This function is used to group the data by one or more variables. Since the task is to compute an average per student, grouping by sid is the correct approach to create subsets of each student’s records before summarisi......Login to view full explanation