Research Methods as techniques or procedures essay

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Question Description

Type you answers in Word and when answering statistical calculations, use Megastat output in Excel.

Make sure you show all work not just answers. Submit both the Word file and the Excel file containing all the MegaStat output. If you have any questions please let me know.

-Part One

Essays Questions

Type answer in a Word file, Single spaced no greater than 12 font and length should be at least a 1.0 pages (not including bibliography).Use Turabian citation methods throughout. Only use book Applied Statistics for Public and Nonprofit Administration 9th edition by Kenneth J. Meier; Jeffrey L. Brudney; John Bohte as a resource to answer questions if using quotations or the attachments provided.

1.John Grix (2002) defined research methods as “techniques or procedures used to collate and analyses data.”Explain what type of ontological and epistemological perspectives inform statistical (quantitative) methods. You are to only use Meier & Brudney text, the Grix, and Collier & Brady materials (please see attachment below) to answer this question.

2.Explain which type of analysis, what Collier & Brady describe as “thick versus thin analysis” statistical methods relies upon. Why? You need to use several statistical tests & methods to answer.

-Part Two

3. Use Megastat statistical software to perform the following analyses from the Problem 3 is based on data & information included in the dataset titled Homework Data

a)For the variable “Unemployment Rate” produce a frequency distribution and histograms using Megastat.

b)Megastat will default a frequency distribution upon highlighting of the input range and selecting “OK” button to execute the statistics on the data. Include this default frequency distribution and histogram. Write a short paragraph in which you describe the shape of the distribution and summarize the distribution in general terms.

c)Go back and adjust the interval width. You can alter it by typing in your own interval width on the “equal width intervals” tab. Does this help you describe the shape of the distribution? Why or why not?

4. Use Megastat statistical software to perform the following analyses from the Problem 4 is based on data & information included in the dataset titled Homework Data attached below. Submit all Megastat output along with your statistical interpretation (place answer 4b in the same world file with rest of answers).

a)For the variable “ % Poverty” compute the mean, median, standard deviation, IQR or interquartile range, the 25th & 75th percentiles, apply the empirical rule using Megastat and do an outlier analysis if applicable.

b)Based upon these statistics write a short analytical report of what you found for EACH statistic interpreting them. Remember to interpret any numeric value in the language of the variable.


5. Use the variable “%BS or Higher” in to complete the confidence interval problem. Use Megastat statistical software to perform the following analyses from the Problem 6 is based on data & information included in the dataset titled “Homework Data.”Submit all Megastat output along with your statistical interpretation.

a)Go to MegaStat-Confidence intervals/Sample Size and pull up the dialogue box.

b)In the Confidence interval-mean tab type in the mean score from the population of Midwest states on the variable “%BS or higher.” Use MegaStat to calculate your mean score.

c)Next, you must select the “t” or “z” distribution- click with mouse. Explain why you chose “t” or “z” distribution.

d)Calculate the confidence interval and type up in your Word file the interpretation.

6. Use the variable “% Poverty” in problem 4 to complete the sampling problem. Randomly sample 3 states with years and then compare the mean score of the sample to your full population of mean “% poverty” you calculated in problem 4.

a)Include the output of the three states chosen, if you get a state twice, replace with another randomly selected state( use Base Excel to quickly randomly sample 3 states) . A short couple of sentences should be included to describe your process. Use the Data Analysis feature in Excel to do the sampling and the Descriptive Statistics feature in Megastat to do the three state “% poverty” mean calculation.

b)If the mean scores are similar or dissimilar use the idea of the sampling distributions of sample means to attempt to explain the differences or similarities you find.

Unformatted Attachment Preview

Observation Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 % BS or % Unemployment State higher* Poverty Rate MO 24.3 13.8 4.87 MO 24.5 13.3 5.08 MO 25.0 13.5 6.18 MO 25.2 14.6 9.26 MO 25.6 15.3 9.58 MO 26.1 15.8 8.49 MO 26.4 16.2 6.98 MO 27.0 15.8 6.73 MO 27.5 15.5 6.13 MO 27.8 14.8 4.99 MO 28.5 14.0 4.58 KS 28.6 12.2 4.39 KS 28.8 11.2 4.24 KS 29.6 11.3 4.63 KS 29.5 13.2 6.87 KS 29.8 13.5 7.06 KS 30.1 13.8 6.49 KS 30.4 14.0 5.73 KS 31.1 13.9 5.31 KS 31.5 13.5 4.53 KS 31.7 12.9 4.15 KS 32.8 12.2 4.03 IL 28.9 12.3 4.57 IL 29.5 11.9 4.96 IL 29.9 12.2 6.31 IL 30.6 13.3 10.20 IL 30.8 13.8 10.37 IL 31.0 14.9 9.69 IL 31.6 14.7 8.99 IL 32.1 14.6 9.04 IL 32.8 14.3 7.10 IL 32.9 13.6 5.97 IL 34.0 13 5.82 NE 26.9 11.3 3.13 NE 27.5 11.1 3.00 NE 27.1 10.8 3.34 NE 27.4 12.2 4.64 NE 28.6 12.6 4.63 NE 27.9 12.9 4.39 NE 29.0 12.8 4.02 NE 29.4 12.9 3.77 NE 29.5 12.3 3.27 NE 30.2 12.2 3.02 *% BS or higher= population with a 4 year university de 2016 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 NE MN MN MN MN MN MN MN MN MN MN MN WI WI WI WI WI WI WI WI WI WI WI 31.4 30.4 31 31.5 31.5 31.8 32.4 33.2 33.5 34.3 34.7 34.8 25.1 25.4 25.7 25.7 26.3 26.5 27.1 27.7 28.4 19.6 20.8 11.3 9.7 9.5 9.6 10.9 11.5 11.8 11.4 11.2 11.4 10.2 9.9 10.9 10.8 10.5 12.4 13.2 13.1 13.2 13.5 13.2 12.1 11.8 3.09 3.99 4.57 5.44 7.77 7.41 6.49 5.62 4.97 4.18 3.68 3.87 4.74 4.89 4.93 8.58 8.64 7.76 7.03 6.70 5.42 4.53 4.01 th a 4 year university degree or higher (includes B.A. as well). P O L I T ICS: 2002 VO L 22(3), 175–186 Introducing Students to the Generic Terminology of Social Research Jonathan Grix Institute for German Studies University of Birmingham The aim of this article is twofold: first, to present an accessible way of introducing students to the key generic terms of social science research. There is an obvious need for clarifying the generic tools and terminology of the social sciences across the disciplines, as academics argue past each other, using identical terms but attaching different meanings to them. Secondly, this article presents the interrelationship between the core concepts of social science (ontology, epistemology, methodology, methods and sources). This ‘directional’ and logical relationship needs to be understood, if students – and academics – are to engage in constructive dialogue and criticism of each others’ work. Introduction Given the variety of uses of the terms and terminology of social science research, it is hardly surprising that students rarely have a firm grasp of the tools of their trade. Different academics in different disciplines attach a wide range of meanings and interpretations to the terminology of research. It is my contention that before students actually get down to research they need to be exposed to the ‘building blocks’ of generic social research, that is, the basic language of research that comes before they are trained in disciplinary traditions. This may sound trivial, but given the fact that many students – and seasoned academics, for that matter – have difficulty in differentiating between crucial terms such as ontology (that is, what is out there to know about) and epistemology (that is, what and how can we know about it), their subsequent research is bound to suffer, as knowledge of these terms and their place in research is essential to understanding the research process as a whole. In addition to discussing terminological clarity in the social sciences, the following article intends to show the importance of the interrelationship between the core components of the research process: ontology, epistemology, methodology, methods and sources.1 It is therefore against this background – and the fact that research councils, most notably the ESRC (Economic and Social Research Council), have pushed for an increase in formal research training at postgraduate level – that this article sets out a way of introducing students to the fundamental tools of research in a clear and understandable manner. I start by outlining why it is necessary to learn the tools and terminology of research. The important terms ontology and epistemology, for example, are often shrouded in mystery, partly created by the language with which they are explained, leaving the reader more confused than they were before they © Political Studies Association, 2002. Published by Blackwell Publishers, 108 Cowley Road, Oxford OX4 1JF, UK and 350 Main Street, Malden, MA 02148, USA 176 JONATHAN GRIX began reading. Once students are clear about the basic terms, it is important to get across to them the interrelationship of a researcher’s ontological position with other key components of the research process, namely epistemology, methodology, methods and even sources. After a discussion of the ‘directional relationship’ (Hay, 2002, p. 63) between these concepts, I present an example using the current debate around the term ‘social capital’ to reveal how this works in practice – that is, how a particular ontological position impacts on, and affects, the subsequent stages of research. Learning the tools of the trade Why do we need to know and understand standard terms and concepts in social science? A simple example will suffice: consider a would-be bricklayer who does not know the difference between a trowel, spirit level and a chisel. These are the basic tools of his trade, without which no wall can be built. Each tool has a specific purpose and, if used wrongly (or in the wrong order), for example taking a chisel to lay bricks, the results would be disastrous. In research, specific tools have specific purposes and, if one is to employ them correctly, one must first understand what they mean, what they are meant to do and how and when to use them. The lack of clarity and constancy of the social science lexicon has led to a minefield of misused, abused and misunderstood terms and phrases with which students must contend.2 More importantly, a clear and transparent knowledge of the ontological and epistemological assumptions that underpin research is necessary in order: (1) to understand the interrelationship of the key components of research (including methodology and methods); (2) to avoid confusion when discussing theoretical debates and approaches to social phenomena; and (3) to be able to recognise others’, and defend our own, positions. I would like to reflect on these points. Why is clarity and constancy of terms so important? If we, as researchers, are unclear about the ontological and epistemological (see below for fuller definitions of these terms) basis of a piece of work, we may end up criticising a colleague for not taking into account a factor which his/her ontological position does not allow for. For example, criticising a full-blown positivist (if such a person still exists) for not taking into account hidden structures in society (such as patriarchal structures), when his/her ontological and epistemological position does not allow for such things, is a classic case of arguing past one another. Achieving such clarity in social science work presumes not only familiarity with academic terms on our part, but also that researchers whose work we read are explicit about their own ontological and epistemological positions.3 Thus, I contend that students of social research need to understand and grasp the following before undertaking a fully fledged research methods course and before undertaking any research themselves. The best place to start for students – and I believe undergraduates from all social science disciplines, and not just political science and sociology, will benefit from this – is with the terms ‘ontology’ and ‘epistemology’, as these are central to all social research. © Political Studies Association, 2002. THE GENERIC TERMINOLOGY OF SOCIAL RESEARCH 177 Ontology Ontology is the starting point of all research, after which one’s epistemological and methodological positions logically follow. A dictionary definition of the term may describe it as the image of social reality upon which a theory is based. Norman Blaikie offers a fuller definition, suggesting that ontological claims are ‘claims and assumptions that are made about the nature of social reality, claims about what exists, what it looks like, what units make it up and how these units interact with each other. In short, ontological assumptions are concerned with what we believe constitutes social reality’ (Blaikie, 2000, p. 8). With this in mind, it is not difficult to understand how different scholarly traditions embedded in fundamentally different cultural contexts can have diverging views of the world and differing assumptions underpinning their particular approaches to social inquiry. For the current discussion it is important to make students aware of the need to understand, acknowledge and defend one’s own ontological position. An individual’s ontological position is their ‘answer to the question: what is the nature of the social and political reality to be investigated?’ (Hay, 2002, p. 63), an assumption which is impossible to refute empirically (see also Hughes and Sharrock, 1997, pp. 5–6). It is only after this question has been asked and answered that one can discuss what it is that we can know about this social and political reality that is thought to exist (see Epistemology, below). Examples of ontological positions are those contained within the perspectives ‘objectivism’ and ‘constructivism’. Broadly speaking the former is ‘an ontological position that asserts that social phenomena and their meanings have an existence that is independent of social actors’. The latter, on the other hand, is an alternative ontological position that ‘asserts that social phenomena and their meanings are continually being accomplished by social actors. It implies that social phenomena and categories are not only produced through social interaction but that they are in a constant state of revision’ (Bryman, 2001, pp. 16–18). It is clear from these two examples how one’s ontological position will affect the manner in which one undertakes research (see below for a more detailed discussion on this). If ontology is about what we may know, then epistemology is about how we come to know what we know. Epistemology Epistemology, one of the core branches of philosophy, is concerned with the theory of knowledge, especially in regard to its methods, validation and ‘the possible ways of gaining knowledge of social reality, whatever it is understood to be. In short, claims about how what is assumed to exist can be known’ (Blaikie, 2000, p. 8). Derived from the Greek words episteme (knowledge) and logos (reason), epistemology focuses on the knowledge-gathering process and is concerned with developing new models or theories that are better than competing models and theories. Knowledge, and the ways of discovering it, is not static, but forever changing. When reflecting on theories, and concepts in general, students need to reflect on the assumptions on which they are based and where they originate from in the first place. For example, can theories generated in Western democracies properly explain phenomena in East European transition states with a 60-year history of © Political Studies Association, 2002. 178 JONATHAN GRIX authoritarianism? Two contrasting epistemological positions are those contained within the perspectives ‘positivism’ and ‘interpretivism’. These terms can be traced back, and illuminated by reference to, specific traditions in the philosophy of social sciences. Broadly speaking, the former ‘is an epistemological position that advocates the application of the methods of the natural sciences to the study of social reality and beyond’. The latter, on the other hand, can be seen as an epistemological position that ‘is predicated upon the view that a strategy is required that respects the differences between people and the objects of the natural sciences and therefore requires the social scientist to grasp the subjective meaning of social action’ (Bryman, 2001, pp. 12–13). It is clear that choosing one of these epistemological positions will lead one to employ a different methodology than one would otherwise, were one to choose the other. It is also clear to see how a researcher’s ontological and epistemological positions can lead to different views of the same social phenomena. Differing ontological and epistemological views The assumptions underlying research are thus both ontological and epistemological. Plato’s famous allegory of the cave is instructive for making us aware of the root of ontology and epistemology, for it shows how very different perceptions of what constitutes reality can exist. Prisoners in a cave are chained in such a way that they can only see forwards, to a wall, upon which shadows of artefacts, carried by people behind them, are reflected in the light of a fire. The prisoners give names and characteristics to these objects, which, to them, represent reality. Plato then imagines a scene in which one prisoner leaves the dark cave and sees that not only are the shadows reflections of objects, but also that the objects are effigies of reality. In the text, Socrates says (Plato, 1994, pp. 241–242), in conversation with Glaucon: ‘Suppose someone tells him [the prisoner released from the cave] that what he’s been seeing all this time has no substance, and that he’s now closer to reality and is seeing more accurately, because of the greater reality of the things in front of his eyes – what do you imagine his reaction would be? And what do you think he’d say if he were shown any of the passing objects and had to respond to being asked what it was? Don’t you think he’d be bewildered and would think that there was more reality in what he’d been seeing before than in what he was being shown now?’ The passage cited above mirrors how some people can come to think in certain ways, which are bound by certain cultural and social norms and parameters, for example those established by disciplines in academia. Any premises built upon the experience of the cave dwellers are certain to differ from those who are on the outside. It is for this reason that we need to be aware of, and understand, that different views of the world and different ways of gathering knowledge exist. The order in which I have discussed the two terms in this section is important, for ‘ontology logically precedes epistemology which logically precedes methodology’ (that is, how we go about acquiring the knowledge which exists) (Hay, 2002, p. 5). Interestingly, many research-methods books either discuss these terms the other way around (which, to me, is illogical) or avoid explaining them altogether (which makes it difficult to understand the rest of the book). I now take the argument © Political Studies Association, 2002. THE GENERIC TERMINOLOGY OF SOCIAL RESEARCH 179 about the interrelationship of the key research components one step further by suggesting that methodology logically precedes research methods, which logically precede data sources. The directional relationship between ontology, epistemology, methodology, methods and sources It may at first seem somewhat mechanistic and rigid to suggest a directional relationship between the key building blocks of research, but for teaching purposes this simplified overview can help to demystify an often impenetrable discussion. It is of paramount importance that students understand how a particular view of the world affects the whole research process. By setting out clearly the interrelationship between what a researcher thinks can be researched (their ontological position), linking it to what we can know about it (their epistemological position) and how to go about acquiring it (their methodological approach), students can begin to comprehend the impact one’s ontological position can have on what and how we decide to study. Ontology is often wrongly collapsed together with epistemology, with the former seen as simply a part of the latter. Whilst the two are closely related, they need to be kept separate, for all research necessarily starts from a person’s view of the world, which itself is shaped by the experience one brings to the research process. A researcher’s methodological approach, underpinned by and reflecting specific ontological and epistemological assumptions, represents a choice of approach and research methods adopted in a given study. Methodology is concerned with the logic of scientific inquiry; in particular with investigating the potentialities and limitations of particular techniques or procedures. The term pertains to the science and study of methods and the assumptions about the ways in which knowledge is produced. Methodology is logically linked to, and very often confused with, the research methods employed in a project (see also Blaxter et al., 1997, p. 59). The latter are understood here as, quite simply, the ‘techniques or procedures used to collate and analyse data’ (Blaikie, 2000, p. 8). It is because methodology is concerned with the logic, potentialities and limitations of research methods that the term is often confused and used interchangeably with the research methods themselves. The method(s) chosen for a research project are inextricably linked to the research questions posed and to the sources of data collected, as Figure 1 shows. Figure 1 may come across as somewhat prescriptive or, in the words of one reviewer of this article, it may remind readers ‘of old style methods books of the 1950s’. However, I decline to change the figure for two reasons: first, the figure shows the directional, and logical, relationship between the key components of research. What the figure does not show is the impact and influence of the questions one is asking, and the type of project one is undertaking – for example, either researching individuals’ attitudes or institutional change – on the methods chosen. However, it is our ontological and epistemological positions that shape the very questions we may ask in the first place, how we pose them and how we set about answering them. Secondly, I fundamentally disagree with the opinion that research may begin at any of the stages in the figure above, for example that a researcher can first choose a favourite or familiar method and then work back through their © Political Studies Association, 2002. JONATHAN GRIX 180 Figure 1: The interrelationship between the building blocks of research Ontology Epistemology Methodology Methods Sources What’s out there to know? What and how can we know about it? How can we go about acquiring that knowledge? Which precise procedures can we use to acquire it? Which data can we collect? Source: Figure adapted from Hay, 2002, p. 64. methodology, epistemology and ontology. I think we should guard against ‘method-led’ research, that is, allowing ourselves to be led by a particular research method rather than ‘question-led’ research, whereby research questions point to the most appropriate research method. Choosing a research method before having a research question goes against the logic of interconnectedness discussed above and will more than likely result in a poor question/method fit. Methods themselves should be seen as free from ontological and epistemological assumptions, and the choice of which to use should be guided by research questions. In the minds of many researchers, certain methods are inextricably bound up with certain ontological and epistemological assumptions: for example, try asking an en ...
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Q3

Frequency Distribution - Quantitative
Unemployment Rate
lower

upper

3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00

<
<
<
<
<
<
<
<

4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00

midpoint width
3.50 1.00
4.50 1.00
5.50 1.00
6.50 1.00
7.50 1.00
8.50 1.00
9.50 1.00
10.50 1.00

frequency
10
23
8
9
6
4
4
2
66

midpoint width
3.25 0.50
3.75 0.50
4.25 0.50
4.75 0.50
5.25 0.50
5.75 0.50
6.25 0.50
6.75 0.50
7.25 0.50
7.75 0.50
8.25 0.50
8.75 0.50
9.25 0.50
9.75 0.50

frequency
6
4
8
15
4
4
5
4
4
2
1
3
2
2

Histogram
40
35

Percent

30
25
20
15
10
5
0

Unemployment Rate

Frequency Distribution - Quantitative
Unemployment Rate
lower

3.00
3.50
4.00
4.50
5.00
5.50
6.00
6.50
7.00
7.50
8.00
8.50
9.00
9.50

upper

<
<
<
<
<
<
<
<
<
<
<
<
<
<

3.50
4.00
4.50
5.00
5.50
6.00
6.50
7.00
7.50
8.00
8.50
9.00
9.50
10.00

10.00

Histogram
25

Percent

20
15
10
5
0

Unemployment Rate
Q4

Descriptive statistics
count
mean
sample standard deviation
sample variance
minimum
maximum
range

% Poverty
66
12.683
1.601
2.562
9.5
16.2
6.7

empirical rule
mean - 1s
mean + 1s
percent in interval (68.26%)

11.083
14.284
68.2%

mean - 2s
mean + 2s
percent in interval (95.44%)

9.482
15.885
98.5%

mean - 3s
mean + 3s
percent in interval (99.73%)

7.881
17.485
100.0%

1st quartile
median
3rd quartile
interquartile range
mode

11.400
12.850
13.750
2.350
12.200

< 10.50

10.25

0.50

2
66

BoxPlot
3-9-2019 14:48.59 (1)

8

9

10

11

12
13
% Poverty

14

Q5

Descriptive statistics
count
mean
sample standard deviation
sample variance

% BS or higher*
66
29.064
3.144
9.886

Confidence interval - mean
95%
29.064
3.144
66
1.997
0.773
29.837
28.291

confidence level
mean
std. dev.
n
t (df = 65)
half-width
upper confidence limit
lower confidence limit

15

16

17

percent
15.2
34.8
12.1
13.6
9.1
6.1
6.1
3.0
100.0

percent
9.1
6.1
12.1
22.7
6.1
6.1
7.6
6.1
6.1
3.0
1.5
4.5
3.0
3.0

cumulative
frequency percent
10
15.2
33
50.0...

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Anonymous
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