Assignment Three: Analyzing Quantitative Data
List of Figures
Figure 1 Frequency per rank for the top 100 words 3
Figure 2 A histogram showing the distribution of token size across the "Doctored Dataset" Corpus 7
Figure 3 A boxplot showing the distribution of token size across the "Doctored Dataset" Corpus 7
Figure 4 A Q-Q plot of the distribution of token size across the "Doctored Dataset" Corpus 8
Figure 5 A boxplot showing the median length of research articles in each disciplinary domain 8
Figure 6 A boxplot showing the descriptive statistics in five academic domains 11
Figure 7 A scatter plot showing the correlation between the numbers of tokens and types across the five domains 12
List of Tables
Table 1 Descriptive
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This simply means that the majority of words occur only a few times. Another evidence of this conclusion is the median frequency which is 2.00.
Question 3 Figure 1 Frequency per rank for the top 100 words
Figure 1 is a line graph that shows the correlation between the frequency (y) and the rank (x) of the top 100 most frequent words in the pre-mentioned academic corpus. As in Zipf’s Law, the frequency of a word in a corpus of natural language is inversely proportional to its rank in the frequency table. That is, the most frequent word occurs approximately twice as often as the second most frequent word, three times as often as the third most frequent word, etc.
Question 5
The table below shows a Chi-square test of the use of the word ‘lovely’ in both COCA: spoken and BYU-BNC: spoken corpora Lovely All other words Total words
COCA: spoken 1836 90063928 90 065 764
BYU-BNC: spoken 2397 9961266 9 963 663
Total 4233 100025194 100029427
Table 2 The use of
233). Reading and reading comprehension is a basic skill that scholars will be able to use all along their lives and it all start here by encoding, decoding, adding and deleting sounds. This research will make use of CVC as a beginning set of letters that five year olds start manipulating nth verbally and in writing.
B.Students’ reading comprehension will depend almost entirely on their word recognition skills; their prior knowledge won’t make much of a difference.
Clay, M. M. (2002). 'Taking records of reading continuous texts'. In M. M. Clay, An
The inventory should be individually administered to students in order to accurately observe student automaticity with the high-frequency word recognition. Elementary students are frequently given this test in order to progress monitor high-frequency word mastery and general factors of fluency.
There is reliable and dependable proof for first-letter access, there is only weak confirmation for syllable access. In both experiments, syllable figures did not contrast across confidence levels and a higher coincidence at confidence levels in the research. (Brown and Burrows, 2013). A Mnemonic is utilized to recollect, and it could be a phrase, a short song, or something easily recalled, and it can assist the individual in finding something that is difficult to remember. For instance, we may use a phrase like PEMDAS, which means, Please Excuse My Dear Aunt Sally". It stands for "Parentheses, Exponents, Multiplication and Division, and Addition and Subtraction".
In chart (i), “Dataset B” appears to be at least partially contrastive since there is a partial minimal pair, ɡlæs ‘glass’ and kleʌs ‘class’. The [æ] and [eʌ] both appear in the [l_s] environment, indicating that there is an overlap.
It is very interesting how he could find many examples of corporations and important people stating words with no meaning. To me this surprised me the most because I realized how easily one can be fooled. He explained it as clutter; “the official language used by corporations to hide their mistakes” (15). It is amazing how so many presidents, senators, among other people who lead the country fool the majority of the population by twisting complex words around. The one that most impacted me was when President Ford told a group of businessmen: "We see nothing but increasingly brighter clouds every month."(On Writing Well, 23). His statement was very vague yet everybody saw hope. It is amazing to see the power words
In The Secret Life of Pronouns by James W. Pennebaker, Pennebaker conducts many experiments to understand the effect word choice has on a person’s disposition and mental health. While Pennebaker often refers to the data collected by Linguistic Inquiry and Word Count (LWIC), however many students have conducted experiments that he draws conclusions from. Cheryl Hughes, a student at Southern Methodist University, conducted an experiment on students to see the effect of forced word choices had on their health. While some students were required to use negative emotion words while others had positive words, there was no visible difference in the health of students. Pennebaker concludes that “simply requiring people to use the words at higher rates
This study is a conceptualized replication of the Howes and Solomon (1951) experiment investigating word accuracy and word frequency in short duration trials. It is hypothesized that words that appear more often in printed text (easier to access in the lexicon) will be more accurately identified rather than words that appear less commonly. A total of 83 participants in the study were presented with words taken from the Throndike-Lorge database. The words were presented for one second with a six second rest in the middle. This was done sixty times and the results suggest a moderate strong relationship between word accuracy and frequency. Though there are multiple factors that may have influenced these results.
I watch “J” and his brother play. Mommy A asks “J” to tell me what he has on the back of his leg. “J” says, “I have Imatiga” Mommy “A” says “He says he has impetigo but it’s just a mosquito bite.” As she states this, “J” gets mad and yells, “NO I HAVE IMATIGA” As I listen to “J” I noticed he like the word impetigo, but was saying it as “im a tiger”, thus having mom use segmentation “breaking up of words into smaller units” (Gleason/Rather 2013. p. 340) to break the word down to “im pa ti go” so “J” could say it correctly, but it was still interesting to hear him talk into my smart phone and the phone show him pictures of tigers.
Increasing the number of words isn’t enough because the speech recognition system is unable to differentiate words like ‘to’ and ‘two’ or ‘right’ and ‘write’ (6 ,p.98).
Alternative research, carried out by Lehiste in 1974, concerned the rate of speech when phrases contain a larger number of words. Lehiste found out that the duration of words in the sentence “Say… instead” was longer than the same word in the sentences “Sometimes it’s useful to say the word … instead” and “The word … is sometimes a useful example”. She concluded that the length of the utterance had a greater effect on the duration of the words than the number of syllables preceding or following the word. Lehiste also
In our work, words were treated as a feature on three levels: using a bag of words form, word stem, in which the suffix and prefix were removed and word root. With all these features we need to extract and generates the frequency list of the dataset features (single words) and save it in a training file.
Another study by (Ben Verhoeven &WalterDaelemans, in 2014) designed to serve multiple purposes: disclosure of age, gender, authorship, personality, feelings, deception, subject and gender. Another major feature is the planned annual expansion with new students each year. The corpus currently has about 305,000 codes distributed on 749 documents. The average
The purpose of this section is to analyze the decreasing value of the production in frequency between the three types of the bigram syntactic sequences and the three types of the trigram syntactic sequences in order to test Hypothesis 2 which was proposed for this study. Hypothesis 2 denotes that, in the learner’s corpus, as compared to the reference corpora, the production rate of the articles is lower in the NPs which have an adjective preceding a noun (Art + Adj + N) than noun phrases which have no preceding adjective (Art + N),