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80 Cards in this Set

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-relate to the principles of right and wrong

-codes of ethics

-moral standards

Predominant ethics philosophies




-based on consequences

-J. Locke



-I. Kant

Unethical research examples

-Nuremburg Medical Studies

-Tuskegee Syphilis Study

Experimental conduct codes

-Nuremburg Codes

-Helsinki Declaration of 1964

-Belmont Report

Belmont Report

-respect for human dignity



Beaumont and Childress





Ways to ensure that research is ethical

-follow professional association guidelines

-obtain Institutional Review Board (IRB) approval

Researchers must inform participants about


-ability to decline







Protecting human rights in sport management


-ability to decline/volunteer



-protection from harm




Elements of an informed consent form






-risks & benefits






Classical levels of measurement






-data are given names or categories

-mutually exclusive

-least quantifiable


-data are given names or categories

-not mutually exclusive, but are ordered

-only indicate more-or-less relationship; unequal distances


-data are given names or categories

-not mutually exclusive, but are ordered

-meaning beyond indicating more-or-less relationship; equal distance

-no inherent starting point


-data are given names or categories

-not mutually exclusive, but are ordered

-meaning beyond indicating more-or-less relationship; equal distance

-no inherent starting point

-most quantifiable

Measurement criteria in sport management research






-internal consistency

Reliability as stability

-same test to same person over time


-intra-rater reliability

Reliability as equivalence

-equivalent test to same person over time

-parallel form

-inter-rater reliability

Reliability as internal consistency

-instrument dependability

-alpha coefficient**, split-half, odd-even, KR20






Validity as face/content

-panel of experts determine if test is measuring what it should be

-CVR = (n-N/2)/(N/2)

Validity as criterion

correlation between new scale of measurement and trait

Validity as construct

relationship between measures

Does reliability equal validity?

It is a pre-condition, but no


enduring disposition to respond consistently

Components of attitudes




Measurement techniques in attitude research



Semantic differential scale

-affective component

-words rather than numbers

Likert scale

-affective component

-summated to produce an index

Questionnaire development process

-define the objectives

-decide a format

-write the questions

-review the questionnaire

-pretest the questionnaire

-revise and finalize the questionnaire

-gather data

-analyze data

Writing the questions


-choice order

-dealing with don't know or n/a responses

Double-barreled question

Measuring two things in one question by use of the word "and"

Leading questions

Questions leading participants to choose an answer they think is right, e.g. "Don't you think...?"

Prestige bias

Respondents answer questions to feel better about themselves


An answer to one question leads to another

Questionnaire flow

-gain interest


-most thought-out


Approaches to sampling



Non-probability sampling

-advantage - less time and money

-disadvantage - no way to analyze the probability for selection; less sophisticated




Probability sampling

-every unit has an equal chance of selection

-advantage - more accurate representation

-disadvantage - more time and money

Data preparation and analysis process




-data entry and analysis


-confirm data collection took place

-survey measured what it needed to

-10-20% participants to be contacted


-questionnaires filled out properly and completely



Field editing

-first stage

-data is accurate, complete, and usable

Central editing

-no ambiguity

Editing process involves





-missing by logic

-missing by design

-missing item

-refusal to respond

-don't know

-inadequate response


assigning numeric codes to responses

Coding process involves

-list all responses

-review responses

-assign numeric code

Coding principles






-extract units of information from numerical data





Descriptive statistics

summarize large volumes of data

Inferential statistics

draw conclusions about a large volume of data

Parametric statistics

-conclusions about a population normally distributed, equal variance

-interval or ratio

Nonparametric statistics

-determines relationship

-ordinal or nominal

Null hypothesis


-no differences between variables

Alternative hypothesis


-statistically significant difference between variables

Directional hypothesis


-alternative hypothesis

-identifies where or under what conditions the difference will occur

Research questions



Difference research questions

comparing differences between two or more groups

Relationship research questions

-mathematical equation is used

-assesses the degree of relationship

Statistical significance

extremely unlikely to have happened by chance (p<.05)

Data analysis techniques

-Describing statistical data as frequency distributions graphic presentations measure of central tendency measure of variability measure of relative proportions

Describing statistical data as frequency distributions

-determine the number of groups or classes

-establish the width of each class grouping

-determine the class boundaries for each class

-count the number of values in each of the class intervals

Describing statistical data by graphic presentations

-bar graph (nominal)

-histogram (ordinal, interval, and ratio)

-frequency polygon (interval and ratio)

-pie chart (nominal)

Describing data by measures of central tendency




Describing data by measures of variability



-standard deviation

Describing data by measures of relative proportions


-percentile range

Factors affecting the selection of a communication method



-writing standards

-time for oral

-space for written

Types of reporting






-findings & conclusion


Short report

5-10 pages

Long report

follows a specific writing manual

Sections of research report







Research reports consist of


-cover letter

-title page

-executive summary





-findings & discussion



-tables, figures, and charts


Poster presentation size


Oral presentation size

10-50 people

APA requires what as far as language?


Styles of writing



-Chicago Manual of Style