• Standard Deviation (S.D. or o)
  • Average deviation of each observation from precise centre of all weighted observations, but sensitive to relative weights of observations.
    • Indicates how dispersed points are from the mean
    • More precise than mean deviation; preferred.
• Example:
  • David Demers….
    • N = 198 newspapers
    • M = 2.64 editorials
    • o = +/- 1.84
    • Range = 0 – 8
    • Standard deviation tells us that the amount of editorials/paper is not around 2.64, but between the dispersion of 0.8 and 4.48 (2.64 +/- 1.84)

Bivariate Statistics

• Analysis of two sets of data
• Coefficient of Correlation
  • Indicates extent to which ordered pairs of observations share variance
  • It gauges if the behaviours of two phenomena are related.
    • Example
    • If x happens, does y happen?
    • If x happens, how much does y happen?
• For correlation and scatter points:
  • Ordered pair = two related numbers (x, y)
  • Examples:
    • (x,y) [scatter plot of x and y analysis, use excel]
      • Hours of television, hours of radio
      • Age, hours of television
      • Education (coded?), hours of radio
      • Age, education.
• Coefficient of correlation or Pearsons r
  • “Coefficient” = measure of strength of correlation expressed as r = + z or – z
    • 0-10 (no correlation)
    • 10-30 (slight degree of relationship)
    • 30-50 (fair degree of relationship)
    • Common knowledge…
• Descriptive Statistics àCorrelation of Coefficient
  • Can do
    • Flag significant data (e.g. highs, lows, averages)
    • Reveals patterns
    • Suggests relationships between values
    • Indicate strength relationship between two values
  • Can’t do
    • Provide explanations
    • You must provide the explanation

Cool Related Sites:

On SEOMOZ “Knowledge” about Statistics « IR Thoughts
Statistics for Business and Economics « Khmer Campus – for unde..
Language Log » Physiological politics
Data Analysis Part 1: Database Management, Distributions, and Bivariates &l..
A Little Primer on Multicollinearity « DemocraticPeace Blog
Good Government vs. Less Government « The Baseline Scenario

Descriptive and Bivariate Statistics is a post from: The Glaring Facts

• A combination of a first-person and a second-person account, which takes place in a naturalistic setting, of the actions and behaviours of a specific group of people
• Most common in communications/cultural studies à is a participant observation (qualitative research)

Observation Research: Uses

• Examine structure and functions of social formation
• Learn components and operations from inside (functionalist)
• Example
  • Actual operations of news rooms, how do they assemble the news? How are they affected by budget cuts?
• Examine culture of social formation
  • Learn cultural or ideological aspects (aka ethnography) à interpretive
  • Example
    • The culture of news rooms
    • All have same tastes, why are they different?
• Examine how structures affect outcomes
  • Watch how product is created, from start to finish
• If using any specific social information as case study of larger social phenomenon
• Major assumption
  • Social formation is representative of all similar formations
  • Intangible qualities of social formation are representative of all similar formations
  • Knowing something about this social formation tells us something about all similar social formations

Observation Research: Advantages

• working with specific social formation you wish to study (reliability – primary data)
• Extraordinarily source of data, more than any other method everything you observe, hear, smell is data (reliability – difficult to fake, highly detailed)

Observation Research: Disadvantages

• fewer sources / less data collected than surveys (reliability – data may be idiosyncratic to social formation)
• Best conducted by lead researcher, bring expertise to the field (cost/time – cannot be done quickly)
• Cannot be used with unwilling/at risk populations (access/ethics – cannot force people to participate

How to Conduct Observational Research is a post from: The Glaring Facts

Survey research : definition

• Broad-based, qualitative and/or quantitative research which collects data through pre-formulates question in a structured questionnaire to a representative sample of individuals drawn from a defined population
• main advantage is number of participants processed
• response / data can be recorded verbatim or coded for statistical analysis

Survey research : use

• Research intangibles
  • as with interviews and focus group
• Research material objects
  • • necessary when no other source of data available (e.g. new rapidly changing technology very fast moving trends)
    • major assumptions:
      • 1) individual or group is representative of entire population
      • 2) intangible qualities of individual or group are representative of entire population
      • 2) knowing something about individual or group tells us something about entire population
  • Organizational studies
    • provides view of organization from the perspective of employees rather than management
    • survey can ensure anonymous and thus confidential responses from people concerned about speaking truthfully

Survey research: Advantage

• Contact period with each participant is brist
  • speed- faster than focus groups
• 2) can be conducted by assistants
  • speed- faster than focus group
  • cost – less expensive
• 3) can fit method to participants
  • access – easier to recruit volunteers

Survey Research: Disadvantages

• Reliability – data be superficial, inconclusive
• Lack of historical perspective. “snapshot”

Process

1. define the research problem
2. review the literature
3. design your research problem

Treatment of Human Subjects

• Ethical consideration
  • do not place your participants at any risk
  • propriety and modesty
  • treat your participants with dignity and respect

Sample strategy

• participants must be able to answer your research question for representative sample, must know entire populatin
• set sample guidelines in relation to analytical categories (i.e. quota for each demographic you need for sample)
• recruit participants until each quota is filled
• result will be a stratified random sample

Sample size

• Considerations
  • nature of research question
  • number of analytical categories

Setting and Timing

• Location of response can affect quality of data collected
• Timing of response can affect quality of data collected
  • Considerations
  • Comfort of participants (including ethical issues)
  • Access to communication
  • Distractions
• Establish an interpretive context
  • a) specific participants used
  • b) mode of interpretation
  • as always, justify your research decision
• Draft a questionnaire
  • Questionnaire- pre-determined list of questions to be answered by each participant (resembles coding schedule for content analysis)
    • brevity is important
    • typically, identify questions first
  • analytical questions follow
    • closed questions: all possible answers listed
    • open questions: black space for expected answers
    • research question: why science fiction a popular genre?
  • be cautious regarding the order of questions
  • don’t lead your respondents to provide specific responses, doing so will taint data, make it less reliable solution. Arrange the same questions in two or more ways, this reduces and/or guages the effect of bias in the order
• Collect Data
  • use your sampling method and questionnaire
• Data preparation and analysis
  • organization answers in most appropriate way
  • can count responses, as in content analysis
    • can create time line, as in historical research
    • can group data into themes, as in policy research
    • look for signposts and patterns
    • explain the patterns

How To Conduct A Survey Research is a post from: The Glaring Facts

• Interdisciplinary field
• No solid ground-work for field
• Some scholars feel that communications research is bullshit.
• Violent TV => Violent people?

Possible Problem areas for research

• “Policy institute,” and “think tanks” is the integrity of their research at risk?
• C.D Howe Institute (Right) vs. Canadian Centre for Policy Alternatives (Left)

Five Principles of Research

• Systematic
  • Carefully consider the accounts for all possible variations
• Disciplined
  • “respect for the evidence” discovered rather than falling back on assumptions.
• Verifiable
  • Any discovery should be replicable by other researchers under the same conditions.
• Cautious
  • The researcher should not claim that finding applies anything beyond what was established in the research.
• Value-Free
  • The personal opinions of the researchers should not affect the outcome of the research itself.

Francis Bacon -> Organizing slowly, carefully and methodically. The Great Instauration (1620). Minute answers contribute to peel away at knowledge.
Dolly the Sheep
Auguste Comte –> Systeme de politique positive. Positive philosophy, positivistic position.

Francis –> Auguste similar because:

• Empiricism: A philosophical position which privileges evidence derived from the 5 senses, or observations, over everything else.
• Empirical Questions: Those which can be answered, can be measured.
• Research in the Humanities: Subjective but still have the potential to succeed in the 5 principles of research. Intangible array of bullshitness.

Value-Free –> Impossible!
No one can separate objectivity from subjectivity.

The case against “value-free” research (A.K.A. Objectivity)

• We use language – words – to describe and organize the world beyond ourselves.
• Words are not natural, words are simply symbols invested with specific meanings
• These symbols bear no direct relationship to the world beyond us (e.g. chair, chaise).
• Our understanding of the world is necessarily mediated by the language we use to describe it.
• Hence, we have no direct knowledge of the world beyond ourselves, and we cannot claim to know absolute truths about it.

Objective Research

• To evaluate research from a neutral perspective without any bias or preconceived notion.
• That is, the research must exclude his/her personal inclinations and try to observe the world as it really is and as it appears to all people.

Subjective Research

• To evaluate data while acknowledging one’s own perspective/bias.
• That is, the researcher does not exclude his/her own personal inclinations, and denies it is possible to observe the world in any other way. That every person sees the world from their own perspective.

Reliability and Validity

• Research is reliable if the findings are acceptable and can be replicated by others.
• Research = valid if the findings can be applied to real-world situations and not just an artificial environment.

Principles of Research is a post from: The Glaring Facts

Content Analysis – Definitions and uses

1. Content analysis: “a research technique for the objective, systematic, and quantitative description of the manifest content of communication.” If something is manifest, its clear to our senses
2. Manifest: something clear and obvious
3. Content of Communication: the message
4. Manifest Content: any plainly recognizable message – i.e. words, pictures, codes, gestures (Such content can be recorded in any medium)
5. Mass Media: print, audio recording, film and video
6. Fine Arts: painting, symphony, sculpture organizational communication: pamphlets, memos, email, reports personal communication: diaries, letters, postcards
7. Objective: without personal bias, or free of subject opinions
8. Systematic: guided by pre-arranged method, mechanical, thorough, not arbitrary. Many researchers believe objectivity is no longer possible; therefore, most go for systematic. No arbitrary decisions regarding data; just pulling info.
9. Quantitative: data is coded to facilitate measurement, or statistical understanding
   1. Coverage of the homeless in newspapers
      • Which newspapers?   … four Toronto papers (4)?
      • Time period?   … one year (52 weeks)?
      • Frequency of sample?  … once per week (1)?
      • Number of articles?   … all in each issue (x)?
      • Result: 4×52×1 = 208 newspaper issues, x articles

Content Analysis is a post from: The Glaring Facts

Have you ever come to terms with a time in your life where you were so heavily involved in a group, or culture, that you came to value its objectives, goals and beliefs? In this environment, you are involved in a culture. No matter what kind of culture, it is the meaning-making system which you are a part of. More specifically, the areas of study which concerns these generated meaning-making systems are a part of the social sciences. Within the social sciences, the term that comes is primarily geared towards this phenomenon is called Organizational Culture. An organization is a unit of people who come together with a purpose in mind. Do you remember the time when you joined an athletic team? For example, when I joined a baseball team, long ago, I remember that I joined to have fun. During my time, I did have fun, but also learned that the team required each and every player to be there every game. As part of this mandatory need, this organization’s success depended on our participation. We communicated through shared values and objectives. Studying Organizational Culture will give us a more comprehensive analysis of these groups we are a part of.

Most importantly, organizational culture analyses power relations, member participation, and the methods taken by the unit to reach its goals. Who is in charge? How does the person in charge influence participation? What are the relationships between members? Is there anyone besides the boss who is equally influential? These are but a few condensed questions that are raised in the organizational institution. At the workplace, employees are expected to adhere to management principles, workplace policy, and replicate the values of the organization. In particular, organizations are a part of their environment and thereby influence that environment. For example, government buildings are a central hallmark to the values of a nation. Within this organization, there are underlying procedures of professionalism which may differ from the environment, although the norms and values associated with their democracies are not different from those of the outside.

So what is this fascinating area of study called Organizational Culture? Organizational culture is the study of people in an institution whose shared values, norms and histories are intrinsically associated as part of the cultural framework. This organizational institution may or may not influence the environment. As part of an organizational unit, the underlying objectives of each of our groups could be the same or be entirely different. If we want to analyze how an organizational culture (such as the workplace), we have to break apart values, assumptions, and norms held dearly to that institution. This line of work is called a cultural analysis of organizational cultures. We want to find out how we can improve the way we communicate within an organization. We can do a cultural analysis in two ways: 1) we can be the insider, a part of the organization, or 2) be the outsider, perhaps an investigator looking into the structure of an organization. For example, if a franchise organization is about to collapse because of mismanagement, how can we save it? We can either hire someone from the outside (the outsider) or someone who knows the inner-workings of the organization (the insider) to help us solve the issue. So what are the benefits of the insider versus the outsider? The insider might help us collect some personal details from the employees; it’s certainly a lot easier to get in and you already know the jazz of the organization! But it does have a few disadvantages such as taking for granted some answers, the explanations from the interviewees might be too vernacular, and there could be a lot of bias in it! Our other option is the outsider. So what can the outsider give us that the insider lacked? The outsider can give us a refreshing look at the socialization; he or she is most likely unfamiliar with the organization so he/she might give us a broader look at the inner-workings of the organizational culture. In some cases, the organizational unit might send both types of analysts, outsider and insider, to investigate mismanagement. At the end of the day, the organizational unit insists on performing through strategic means in order to achieve the goal and more, if possible.

Have you noticed that more and more organizations are looking to invest their business efforts across the other side of the globe? If they are to be successful, they would firstly conduct analysis of their preferred area within the country for key factors such as, which I have already noted: 1) norms; 2) values; and 3) histories. Adequate studies of those three abstract terms are beyond importance. The organizational unit maintains a much more efficient work dynamic once it has negotiated similarities between cultures and their respective differences.

Organizational culture is a fascinating area of study. It helps us understand cultures, how they work, and how you can make the most efficient workforce from them. I suggest you give it a look! Thank you for your time and thank you for your patience.

Organizational Culture Defined is a post from: The Glaring Facts

Content Analysis – Univariate Statistics

• Nominal:
  • Numbers assigned to categories to signify qualitative differences
  • Basically, nominal figures simply tell us that two things are different
    • Generated by arbitrary assignment of numbers to categories
    • No bearing to any objective or subjective scale.
    • Examples:
      • In sports, jersey numbers
      • In content analysis, used whenever content coded categorically
      • Hibbarb and Keenleyside
• Ordinal:
  • Numbers assigned to categories to signify preferences
  • Basically, ordinal figures tell us two things are different and that one is better
    • Generated by arbitrary assignment of numbers to categories
    • Have bearing only to subjective scale
    • Examples:
      • In pop culture, rankings arbitrarily assigned to favourite songs.
      • The scale of difference between what is popular and what isn’t\
      • Rank –> Points = Difference.
• Interval:
  • Numbers assigned to categories based on a fixed scale with equal intervals between points.
  • Basically, interval figures tell us two things are different and that one is better but also indicates the scale of difference.
    • Generated by measurement against fixed scale
    • Scale may be subjective or objective
      • Examples:
      • Thermometer, interval between 4 and 5 is the same between 5 and 6.
      • Communications & cultural studies, used in Lykert scales.
• Ratio:
  • Numbers assigned to categories based on a fixed scale with equal intervals between points and a true zero point.
  • Basically, the most powerful – they allow for direct comparisons. Ratio figures tell us two things are different and that one is better and also indicates an absolute difference.
    • Generally by counting
    • Or measure against fixed, objective scale with true zero point.
    • Examples:
      • Age, starts at birth (the zero point)
      • Content analysis, numbers generated by counting responses
• Descriptive Statistics
  • Data set:
    • Data = information gathered by observation
    • Set = all data related to single phenomenon
  • Univariate analysis:
    • Description of a single data set, without reference to any other data set.
  • Frequency (n): number of observations for each response often expressed symbolically as “n”.
  • Range: complete spectrum of observation in a data set. E.g. Grundy = F-A-G. Agazi not.
    • Class marks = 58, 61… 85, 90
    • Range = 58 to 90
    • Range size = 32
  • Median: precise centre of range, regardless of weight observation
    • Example: class marks —– 58, 61… 85, 90
    • Middle number = 70 + 72 = 69
  • Mean or Average: precise centre of the weighted observations
    • Example: class marks — 58, 61… 85, 90
    • Mean = sum/n
    • 1420/20= 71
  • Mean deviation: average difference of each observation from precise centre of all weighted observations.
    • Example: 58, 61… 85, 90
    • Mean = 71
    • Deviation 71-58=13
    • 71-61 = 10, etc…
    • Total sum of deviations = X
    • x/n – 134/20= +/- 6.7
    • Example convoluted
      • Range = 58 to 90
      • Median = 71%
      • Mean deviation = +/- 6.7%

Univariate Statistics is a post from: The Glaring Facts

• Types of intensive, qualitative research which generate data through directed, social interaction
  • interviews involve questioning an individual or group with expertise or experience regarding your subject
  • focus groups involve fostering discussion among groups of people with expertise or experience regarding your subject

Interviews & Focus Groups: Uses

• Research intangibles
• Intangibles = beliefs, values, attitudes, articles of faith, motives, desires ot passions  a.k.a. personal & cultural traits
• In-depth study of particular individual or group
  • sample popular opinion with interviews
  • sample popular opinion with Focus groups
• major assumption:
  • individual or group is representative of entire population
  • intangible qualities of individual or group are representative of entire population
  • knowing something about individual or group tells us something about entire population

Interviews & Focus Groups: Advantages

• interview and Focus groups (primary data)
  • Focus Groups vs. Interviews
    • Cost -less expensive
    • Reliability – Interpersonal vs. group communication
  • Focus Groups vs. Survey/Observation
    • Faster -fixed, brief time-span
    • Cost – Little if no time spent on the field
    • Access – Easier to recruit volunteers
• interviews and Focus Groups
  • Lack historical perspective, “snapshot”

1. Define the research problem
2. Review the literature
3. Select research method
4. Design your research program

Treatment of human subjects

• ethical considerations
  • do not place your participants at any risk
• propriety and modesty
  • treat your participants with dignity and respect

Sample Strategy

• Participants must be able to answer your research question for representative sample, you must know entire population
• Set sample guidelines in relation to your analytical categories (e.g. if religious faith is a category, ensure all faiths represented)
• Each analytical category requires its own stratum
• Once they strategy set, recruit participation until each quota is filled result will be a “stratified” random sample

Sample Size

• Size of focus groups
  • 6-10 people is the optimum number
• Number of focus groups
  • any number of distinct focus groups is possible
  • simple exploration / test question = 1-3 groups
  • main research methods > 3 groups
  • considerations: size of entire population
  • number of analytical categories

Setting

• Location of interview or focus group can affect quality of data collected

Establish an interpretice context

• specific sources and location used
• mode of interpretation
  • as always, justify your research decisions

Draft an Interview Guide

• Interview Guide- Pre-determined list of issues and questions to be addressed during interview (resembles coding schedule for content analysis)
• identify categories first
• Remaining questions second
• Researchers nmust ote time permitted for each question (e.g. 30 sec? 15 min?)

Recruit Participants

• If using focus groups, use your sampling strategy

Collect data

• use your interview guide

Data preparation and analysis

• organize answer in most appropriate way
• can count responses, as in content analysis
• Can create time line, as in historical research
• Can group data into themes, as in policy research
• look for signposts and patterns
• explain the patterns

Interview and Focus Group Research is a post from: The Glaring Facts

Research requires a perspective

• Functionalist
  • Goal: enhancing the function of the main concern — multibake -> looking at productivity and profit of the company. make adjustments after seeing what the problem is. everything else is a variable (e.g. people). goal = efficiency and productivity
• Interpretive
  • Focus is messages
  • Understanding culture
  • Outlook: academic — understanding the way organizational behaviours operate…
• Critical
  • Focus is power
  • Is that power legitimate – Hilary (Multi-Bake) imposing her power on the workers.
  • Leah (girl who resigned) is an informal source of power — she organizes shit and so on – you don’t respect the boss, people don’t work hard. if they share the same goals, the Organization will improve ( e.g. stakeholder theory).
  • Cecil has another form of power
  • Outlook: activist, moralist

Research Perspectives Summarized is a post from: The Glaring Facts

• Quantitative Research
  • Requires data which is numerical/statistical
  • Examples: Content analysis, surveys
• Qualitative Research
  • Involves data which is textual/visual
  • Example: historical research and policy analysis
• Remember
  • They are not mutually exclusive
  • Example: Lewis & Neville on Rosie the Rivetter

History & Policy: Definitions

• “History” : “Record of what has happened in the past” and the past starts now
• “Policy” : Planned rules governing expectations for behaviour; generally administrative, can be public or private, formal or informal
• “longitudinal” : (adj) describing something which occurs over time (e.g. childhood education used by scientists, some social scientists.)

Historical Research: Uses

• Understand how/why something happened in the past
  • Examples:
    • National film distribution policies
      • How did industries develop? Any obstacles? What policies enacted? Effective? Is Canadian situation comparable?
    • How did Canadian film production develop? Who was involved ? How did they work? What stories did they tell?
• Provide background/context for current phenomena
  • Examples:
    • New presidents appointed for a government agency? Who is she? What’s her background? What experience does she have?
  • Assumption:
    • Knowing the past will help us understand the present
    • Knowing the past will help us prepare for the future.
• Understand change
  • Examples:
    • Impact of TV on news/entertainment in 1950s
      • What was available before? How fast did TV spread? Did everyone have access?
    • Demers:
    • Does corporate ownership affect newspaper quality?
  • Assumptions
    • Knowing the past will help us understand the present
    • Knowing the past will help us prepare for the future.
• Understand the past for its own sake
  • “Preentist”: current bias affects historical view
  • “The past is a different country”
    • Examples:
      • Study of magazines and start of consumer culture
      • Use of past to justify the present

Historical Research and Policy Analysis is a post from: The Glaring Facts