A study on relative clauses investigated the frequencies of three types of relative clauses. A small corpus search resulted in 37, 26, and 6 instances of relative clause types RC1, RC2, and RC3 respectively. Your task is to
You have collected data from several different speakers on the
acceptability of particular nouns in the subject (S), direct object
(DO), and indirect object (IO) position. Create this data frame in R and
call it x
:
CASE | SPEAKER | RELATION | NOUN | ACC |
---|---|---|---|---|
1 | S1 | S | x | 4 |
2 | S2 | S | x | 3 |
3 | S3 | S | y | 0 |
4 | S4 | S | y | 5 |
5 | S5 | S | z | 5 |
6 | S6 | S | z | 7 |
7 | S1 | S | a | 5 |
8 | S2 | S | a | 8 |
9 | S3 | DO | b | 3 |
10 | S4 | DO | b | 9 |
11 | S5 | DO | c | 0 |
12 | S6 | DO | c | 3 |
13 | S1 | DO | d | 8 |
14 | S2 | DO | d | 3 |
15 | S3 | DO | e | 1 |
16 | S4 | DO | e | 6 |
17 | S5 | IO | f | 9 |
18 | S6 | IO | f | 8 |
19 | S1 | IO | g | 4 |
20 | S2 | IO | g | 0 |
21 | S3 | IO | h | 8 |
22 | S4 | IO | h | 1 |
23 | S5 | IO | i | 4 |
24 | S6 | IO | i | 5 |
Generate a data frame xx
by resorting `x according
to
Generate two vectors ACC.HI
and ACC.LO
which contain the acceptability ratings which are larger than and
smaller than the mean of all acceptability ratings; then compute the
means of these two vectors.
Show how often which speakers provided ratings larger and equal to / smaller than the overall average rating;
Compute the mean acceptability ratings for subjects, direct objects, and indirect object positions and represent it with a boxplot;
Add a column ACC.GTAV
to x
which, for each
acceptability rating in ACC
, says whether this rating is
larger or equal to / smaller than the average; then cross-tabulate
x$ACC.GTAV
with the x$RELATION
such that
Are the lengths of initial sentences of apologies produced by men generally distributed the same way as the the lengths of initial sentences of apologies produced by women? The data from a small pilot study are stored in <inputfiles/201_11_apologies.csv>.
Are disfluencies more likely in dialogs or in monologs? The data from a small pilot study are stored in <inputfiles/201_04-05_uh(m).csv>.
An interesting phenomenon in English is adjective suffixation with -ic and -ical, especially when both forms are attested. For example, it is difficult to detect any pattern governing the distribution of suffixes: when does an adjective end in -ic only (e.g., acrobatic) and when does it end in -ical only (zoological)? Also, with regard to the adjectives’ general frequency, Marchand (1969) suggested that words in wider common use tend to end in -ical. Your task is to test Marchand’s claim on the data in <inputfiles/201_11_icical.csv> and check whether the average frequency of all adjectives ending in -ical is indeed higher than the average frequency of all adjectives ending in -ic. Note: since I am not providing the exact adjectives, you are allowed to test them not in a pairwise fashion (i.e., politic vs. political, economic vs. economical) but just ‘across the board’, which would of course be less than ideal for a real study.
Is the frequency with which the verb to be is contracted before a progressive verb form (e.g., I’m saying) correlated with the frequency of that same following lexical verb? You expect that the more frequent the verb in the progressive form, the more likely the form of to be will be contracted. The data are in <inputfiles/201_11_contractions.csv>.