Suppose you had a dataset (assigned to df) with 10,000 observations and with a single numerical column called y. 6,995 observations for y are positive; 5 observations for y are NA; and the others are negative (i.e., less than 0). The code should allow you to change the value of y to NA if y is currently negative. If the value of y is currently positive or NA, it should remain unchanged. Some part of the code are redacted. df$y[   A   (df$y    B     )]   C     Complete the code by filling the blanks below.    A    : [Fill in the blank]    B    : [Fill in the blank]    C    : [Fill in the blank] 多项填空题

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Gladly loves figures, so he decides to make a figure showing meatball sales by season. His code is shown below:  d %>%                                           1   ggplot(mapping=aes(x=season,y=meatballs)) +   2   geom_violin() +                               3   geom_jitter(colour=season,alpha=0.4) +        4   theme_bw() +                                  5   scale_fill_brewer(palette="Set1") +           6   labs(title="Meatball sales by season", +      7        x = "Season", y="Meatballs sold")        8 Sadly, there are multiple errors in his code. Which of these lines does NOT contain an error? 

When creating the figure it was necessary to first calculate the summary data. This was done using the code below: d_sum <- d %>%                        1   group_by(location)                  2   summarise(mean = mean(rating),      3             sd = sd(rating),          4             n = n(),                  5             sderr = sd/sqrt(n)) %>%   6   ungroup()                           7 That code may have an error. If so, what line is the error in?

Suppose I have 1,000 simulation results of the sample sum of a chance event, stored under a variable called simulation_result Which of the following codes can I use to produce a cumulative table? The cumulative table should show the number of simulations that had a sample sum of at least a certain number. 

na is a vector of numeric elements. You do not know how many elements na has.  When you run the following, you are returned 1.  sum(is.na(na)) If you execute the following, what would be the output? sum(is.na(na[which(is.na(na))] + na)) ==length(na)

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