1.Describe a recent Gallup poll. Be sure to include the results of the poll, how the poll was conducted, and what the results will be used for 2.Describe a recent study where data was gathered. If possible, explain whether it is a qualitative or quantitative data and whether the data is discrete or continuous. What type of graph would you use to describe the data and why? Solution These results, based on Gallup Daily tracking conducted Aug. 31-Sept. 1, showed predictable partisan differences. Republicans overwhelmingly said the convention made them more likely to vote for Romney, although most would likely be voting for their nominee anyway. Democrats as predictably said the convention made them less likely to vote for Romney. Independents, a key group in any presidential election, were essentially split, with 36% saying the convention made them more likely to vote for Romney and 33% less likely -- although 30% said they don\'t know or that the convention made no difference. Gallup has asked this question after selected conventions going back to 1984. Although the question was asked at differing time intervals after the conventions and in different survey contexts, the results give a rough approximation of the conventions\' relative impact. This historical context shows that the 2012 GOP convention generated about the same impact as the two previous Republican conventions -- in 2008, when John McCain was nominated for president, and in 2004, when George W. Bush was re-nominated. Some methods provide data which are quantitative and some methods data which are qualitative. Quantitative methods are those which focus on numbers and frequencies rather than on meaning and experience. Quantitative methods (e.g. experiments, questionnaires and psychometric tests) provide information which is easy to analyse statistically and fairly reliable. Quantitative methods are associated with the scientific and experimental approach and are criticised for not providing an in depth description. Qualitative methods are ways of collecting data which are concerned with describing meaning, rather than with drawing statistical inferences. What qualitative methods (e.g. case studies and interviews) lose on reliability they gain in terms of validity. They provide a more in depth and rich description. Quantitative methods have come under considerable criticism. In modern research, most psychologists tend to adopt a combination of qualitative and quantitative approaches, which allow statistically reliable information obtained from numerical measurement to be backed up by and enriched by information about the research participants\' explanations. Quantitative data always are associated with a scale measure. Probably the most common scale type is the ratio-scale. Observations of this type are on a scale that has a meaningful zero value but also have an equidistant measure (i.e., the difference between 10 and 20 is the same as the difference between 100 and 110). For exampl.

1. 1.Describe a recent Gallup poll. Be sure to include the results of the poll, how the poll was
conducted, and what the results will be used for
2.Describe a recent study where data was gathered. If possible, explain whether it is a qualitative
or quantitative data and whether the data is discrete or continuous.
What type of graph would you use to describe the data and why?
Solution
These results, based on Gallup Daily tracking conducted Aug. 31-Sept. 1, showed
predictable partisan differences. Republicans overwhelmingly said the convention made them
more likely to vote for Romney, although most would likely be voting for their nominee anyway.
Democrats as predictably said the convention made them less likely to vote for Romney.
Independents, a key group in any presidential election, were essentially split, with 36% saying
the convention made them more likely to vote for Romney and 33% less likely -- although 30%
said they don't know or that the convention made no difference. Gallup has asked this question
after selected conventions going back to 1984. Although the question was asked at differing time
intervals after the conventions and in different survey contexts, the results give a rough
approximation of the conventions' relative impact. This historical context shows that the 2012
GOP convention generated about the same impact as the two previous Republican conventions --
in 2008, when John McCain was nominated for president, and in 2004, when George W. Bush
was re-nominated. Some methods provide data which are quantitative and some methods data
which are qualitative. Quantitative methods are those which focus on numbers and frequencies
rather than on meaning and experience. Quantitative methods (e.g. experiments, questionnaires
and psychometric tests) provide information which is easy to analyse statistically and fairly
reliable. Quantitative methods are associated with the scientific and experimental approach and
are criticised for not providing an in depth description. Qualitative methods are ways of
collecting data which are concerned with describing meaning, rather than with drawing statistical
inferences. What qualitative methods (e.g. case studies and interviews) lose on reliability they
gain in terms of validity. They provide a more in depth and rich description. Quantitative
methods have come under considerable criticism. In modern research, most psychologists tend to
adopt a combination of qualitative and quantitative approaches, which allow statistically reliable
information obtained from numerical measurement to be backed up by and enriched by
information about the research participants' explanations. Quantitative data always are

2. associated with a scale measure. Probably the most common scale type is the ratio-scale.
Observations of this type are on a scale that has a meaningful zero value but also have an
equidistant measure (i.e., the difference between 10 and 20 is the same as the difference between
100 and 110). For example, a 10 year-old girl is twice as old as a 5 year-old girl. Since you can
measure zero years, time is a ratio-scale variable. Money is another common ratio-scale
quantitative measure. Observations that you count are usually ratio-scale (e.g., number of
widgets). A more general quantitative measure is the interval scale. Interval scales also have a
equidistant measure. However, the doubling principle breaks down in this scale. A temperature
of 50 degrees Celsius is not "half as hot" as a temperature of 100, but a difference of 10 degrees
indicates the same difference in temperature anywhere along the scale. The Kelvin temperature
scale, however, constitutes a ratio scale because on the Kelvin scale zero indicates absolute zero
in temperature, the complete absence of heat. So one can say, for example, that 200 degrees
Kelvin is twice as hot as 100 degrees Kelvin From this brief discussion it can be appreciated that
both qualitative and quantitative analyses have something to contribute to corpus study. There
has been a recent move in social science towards multi-method approaches which tend to reject
the narrow analytical paradigms in favour of the breadth of information which the use of more
than one method may provide. In any case, as Schmied (1993) notes, a stage of qualitative
research is often a precursor for quantitative analysis, since before linguistic phenomena can be
classified and counted, the categories for classification must first be identified. Schmied
demonstrates that corpus linguistics could benefit as much as any field from multi-method
research. Qualitative analysis: Richness and Precision. The aim of qualitative analysis is a
complete, detailed description. No attempt is made to assign frequencies to the linguistic features
which are identified in the data, and rare phenomena receives (or should receive) the same
amount of attention as more frequent phenomena. Qualitative analysis allows for fine
distinctions to be drawn because it is not necessary to shoehorn the data into a finite number of
classifications. Ambiguities, which are inherent in human language, can be recognised in the
analysis. For example, the word "red" could be used in a corpus to signify the colour red, or as
a political cateogorisation (e.g. socialism or communism). In a qualitative analysis both senses of
red in the phrase "the red flag" could be recognised. The main disadvantage of qualitative
approaches to corpus analysis is that their findings can not be extended to wider populations with
the same degree of certainty that quantitative analyses can. This is because the findings of the
research are not tested to discover whether they are statistically significant or due to chance.
Quantitative analysis: Statistically reliable and generalisable results. In quantitative research we
classify features, count them, and even construct more complex statistical models in an attempt
to explain what is observed. Findings can be generalised to a larger population, and direct
comparisons can be made between two corpora, so long as valid sampling and significance

3. techniques have been used. Thus, quantitative analysis allows us to discover which phenomena
are likely to be genuine reflections of the behaviour of a language or variety, and which are
merely chance occurences. The more basic task of just looking at a single language variety
allows one to get a precise picture of the frequency and rarity of particular phenomena, and thus
their relative normality or abnomrality. However, the picture of the data which emerges from
quantitative analysis is less rich than that obtained from qualitative analysis. For statistical
purposes, classifications have to be of the hard-and-fast (so-called "Aristotelian" type). An item
either belongs to class x or it doesn't. So in the above example about the phrase "the red flag"
we would have to decide whether to classify "red" as "politics" or "colour". As can be seen,
many linguistic terms and phenomena do not therefore belong to simple, single categories: rather
they are more consistent with the recent notion of "fuzzy sets" as in the red example.
Quantatitive analysis is therefore an idealisation of the data in some cases. Also, quantatitve
analysis tends to sideline rare occurences. To ensure that certain statistical tests (such as chi-
squared) provide reliable results, it is essential that minimum frequencies are obtained - meaning
that categories may have to be collapsed into one another resulting in a loss of data richness.