Research in Business

1
Research in Business
2
Why Study Research?

• Research provides you with the knowledge and
  skills needed for the fast-paced decision-making
  environment

3
Why managers need Better Information

• Global and domestic competitions is more vigorous
• Organizations are increasingly practicing data
  mining and data warehousing

4
The Value of Acquiring Skills

• To gather more information before selecting a
  course of action
• To do a high-level research study
• To understand research design
• To evaluate and resolve a current management
  dilemma
• To establish a career as a research specialist

5
Types of Studies Used to do Research

• Reporting
• Descriptive
• Explanatory
• Predictive

6
Different Styles of Research

• Applied Research
• Pure Research
• Business Research

7
What is Good Research?

• Following the standards of the scientific method
• Purpose clearly defined
• Research process detailed
• Research design thoroughly planned
• High ethical standards applied
• Limitations frankly revealed

8
What is Good Research?

• Following the standards of the scientific method
  (cont.)
• Adequate analysis for decision-makers needs
• Findings presented unambiguously
• Conclusions justified
• Researchers experience reflected

9
The Manager-Researcher Relationship

• Managers Obligations
• Specify problems
• Provide adequate background information
• Access to company information gatekeepers
• Researchers Obligations
• Develop a creative research design
• Provide answers to important business questions

10
Manager- Researcher Conflicts

• Managements limitations exposure to research
• Manager sees researcher as threat to personal
  status
• Researcher had to consider corporate culture and
  political situations
• Researchers isolation from managers

11
Sources of Knowledge

• Empiricists attempt to describe, explain, and
  make predictions through observation
• Rationalists believe all knowledge can deduced
  from known laws or basic truths of nature
• Authorities serve as important sources of
  knowledge, but should be judged on integrity and
  willingness to present a balanced case

12
Scientific Thinking
13
The Essential Tenets of Science

• Direct observation of phenomena
• Clearly defined variables, methods, and
  procedures
• Empirically testable hypotheses
• Ability to rule out rival hypotheses
• Statistical justification of conclusions
• Self-correcting process

14
Ways to Communicate

• Exposition
• Descriptive statements that merely state and so
  not give reason
• Argument
• Allows us to explain, interpret, defend,
  challenge, and explore meaning

15
Important Arguments in Research

• Deduction is a form of inference that purports to
  conclusive
• Induction draws conclusions form one or more
  particular facts

16
The Building Blocks of Theory

• Concepts
• Constructs
• Definitions
• Variables
• Propositions and Hypotheses
• Theories
• Models

17
Understanding Concepts

• A concept is a bundle of meanings or
  characteristics associated with certain events
• Concepts have been developed over time through
  shared usage
• The success of research hinges on
• How clearly we conceptualize and
• How well others understand the concepts we use

18
What is a Construct?

• An image or idea specifically invented for a
  given research purpose

19
Types of Variables

• Independent
• Dependent
• Moderating
• Extraneous
• Intervening

20
The Role of the Hypotheses

• Guides the direction of study
• Provides a framework for organizing the
  conclusions that result

21
What is a Good Hypotheses?

• A good hypotheses should fulfill 3 conditions
• Must be adequate for its purpose
• Must be testable
• Must be better than its rivals

22
The Value of a Theory

• Narrows the range of facts we need to study
• Summarizes what is know about an object of study
• Used to predict further facts that should be
  found

23
The Research Process
24
The Management- Research Question Hierarchy

• Measurement Questions
• Investigative Questions
• Research Questions
• Management Questions
• Management Dilemma

• Level 5
• Level 4
• Level 3
• Level 2
• Level 1

25
Working with Hierarchy

• Management Dilemma
• The symptoms of an actual problem
• Not difficult to identify a dilemma, however
  choosing one to focus on may be difficult

26
Working with the Hierarchy

• Management Question Categories
• Choice of purpose or objective
• Generation and Evaluation of solutions
• Troubleshooting or control situation

27
Working with the Hierarchy

• Fine tune the research question
• Examine concepts and constructs
• Break research question into specific second and
  third level questions
• Determine what evidence answers the various
  questions and hypothesis
• Set the scope of your study

28
Working with the Hierarchy

• Investigative Questions
• Questions the researcher must answer to
  satisfactorily arrive at a conclusion about the
  research question

29
Working with the Hierarchy

• Measurement Questions
• The questions we actually ask or extract from
  respondents

30
Other Process in the Hierarchy

• Exploration
• Recent developments
• Predictions by informed figures about the
  prospects of technology
• Identification of those involved in the area
• Accounts of successful ventures and failures by
  others in the field

31
Research Process Problems

• The Favored Technique Syndrome
• Company Database Strip-Mining
• Unresearchable Question
• Ill-Defined Management Problems
• Politically Motivated Research

32
Designing the Study

• Select a research design from the large variety
  of methods, techniques, procedures, protocols and
  sampling plans

33
Resource Allocation and Budget

• Guides to plan a budget
• Project planning
• Data gathering
• Analysis, interpretation, and reporting
• Types of budgeting
• Rule of thumb
• Departmental or functional area
• Task

34
Evaluation Methods

• Ex Post Facto Evaluation
• Prior Evaluation
• Option Analysis
• Decision Theory

35
Contents of a Research Proposal

• A statement of the research question
• A brief description of research methodology
• Data collection
• Data preparation
• Data analysis and interpretation
• Research reporting

36
Data Collection

• Characterized by
• Abstractness
• Verifiability
• Elusiveness
• Closeness to the phenomenon
• Secondary Data
• Primary Data

37
Final Steps in Research

• Data analysis
• Reporting the results
• Executive Summary
• Overview of the research
• Implementation strategies for the recommendations
• Technical appendix

38
The Research Proposal
39
Purpose of the Research Proposal

• To present the question to be researched and its
  importance
• To discuss the research efforts of others who
  have worked on related questions
• To suggest the data necessary for solving the
  question

40
The Research Sponsor

• All research has a sponsor in one form or
  another
• In a corporate setting, management
  sponsors research
• In an academic environment, the student is
  responsible to the class instructor

41
What are the Benefits of the Proposal to a
Researcher?

• Allows the researcher to plan and review the
  projects steps
• Serves as a guide throughout the investigation
• Forces time and budget estimates

42
Types of Research Proposals

• Internal
• External

43
Proposal Complexity

• 3 Levels of Complexity
• The Exploratory study is used for the most simple
  proposals
• The Small-scale study is more complex and common
  in business
• The Large-scale professional study is the most
  complex, costing millions of dollars

44
How to Structure the Research Proposal?

• Create proposal modules
• Put together various modules to tailor your
  proposal to the intended audience

45
Modules in a Research Proposal

• Executive Summary
• Problem statement
• Research objectives
• Literature Reviews
• Importance of the Study
• Research Design
• Data Analysis
• Nature and Form of Results

• Qualifications of Researcher
• Budget
• Schedule
• Facilities and Special Resources
• Project Management
• Bibliography
• Appendixes

46
What to include in the Appendixes?

• A glossary of concepts, constructs, and
  definitions
• Samples of the measurement instrument
• Other materials that reinforce the body of the
  proposal

47
Evaluating the Research Proposal

• Proposal must be neatly written
• Major topic should be easily found and logically
  organized
• Proposal must meet specific guidelines set by the
  sponsor
• Technical writing style must be clearly
  understood and explained

48
Ethics in Business Research
49
What are Research Ethics?

• Ethics are norms or standards of behavior that
  guide moral choices about our behavior and our
  relationships with others
• The goal is to ensure that no one is harmed or
  suffers adverse consequences from research
  activities

50
Ethical Treatment of Respondents and Subjects

• Begin data collection by explaining to the
  respondent the benefits expected from the
  research
• Explain to the respondent that their rights and
  well-being will be adequately protected, and say
  how this will be done
• Be certain that interviews obtain the informed
  consent of the respondent

51
Deception

• The respondent is told only part of the truth
  when the truth is fully compromised
• To prevent biasing the respondents before the
  survey or experiment
• To protect the confidentiality of a third party

52
Issues Related to Protecting Respondents

• Informed consent
• Debriefing
• Confidentiality
• Right to Privacy

53
Ethical Issues Related to the Client

• Sponsor nondisclosure
• Purpose nondisclosure
• Findings nondisclosure
• Right to quality research

54
Ethical Issues Related to Researchers and Team
Members

• Safety
• Ethical behavior of assistants
• Protection of anonymity

55
Design Strategies
56
What is Research Design?

• A plan for selecting the sources and types of
  information used to answer research questions
• A frame work for specifying the relationships
  among the study variables
• A blueprint that outlines each procedure from the
  hypothesis to the analysis

57
Classifications of Designs

• Exploratory study is usually to develop
  hypotheses or questions for further research
• Formal study is to test the hypotheses or answer
  the research question posed

58
Methods of Data Collection

• Monitoring, which includes observational studies
• Interrogation/ Communication mode

59
The Power of a Researcher

• In an experiment, the researcher attempts to
  control and/or manipulate the variables in the
  study
• In an ex post facto design, the researcher has
  no control over the variables, they can only
  report what has happened

60
What type of Study to use?

• Descriptive is how one variable produces changes
  in another
• Causal tries to explain relationships among
  variables

61
The Time Dimension

• Cross-sectional studies are carried out once and
  the represent a snapshot of one point and time
• Longitudinal studies are repeated over an
  extended period

62
The Topical Scope

• Statistical studies attempt to capture a
  populations characteristics by making
  inferences form a samples characteristics
• Case studies place more emphasis on a full
  contextual analysis of fewer events or conditions
  and their interrelations

63
The Research Environment

• Field Conditions
• Laboratory Conditions
• Simulations

64
A Subjects Perceptions

• Usefulness of a design may be reduced when people
  in the study perceive that research is being
  conducted
• Subjects perceptions influence the outcomes of
  the research

65
Why do Exploratory Studies?

• Exploration is particularly useful when
  researchers lack a clear idea of the problems

66
Data Collection Techniques

• Qualitative Techniques
• Secondary Data
• Focus Groups
• Two-stage Design

67
The Concept of a Causal Study

• The essential element of causation is that A
  produces B or A forces B to occur

68
Relationships that Occur with a Causal Study

• Symmetrical
• Reciprocal
• Asymmetrical

69
Types of Asymmetrical Relationships

• Stimulus-Response
• Property-Disposition
• Disposition-Behavior
• Property-Behavior

70
Achieving the Ideal Experimental Design

• Random Assignment
• Matching
• Manipulation and control of variables

71
Measurement
72
Measurement

• Selecting observable empirical events
• Using numbers or symbols to represent aspects of
  the events
• Applying a mapping rule to connect the
  observation to the symbol

73
What is Measured?

• Objects-things of ordinary experience and that
  are not that concrete
• Properties-characteristics of objects

74
Characteristics of Data

• Order
• Interval between numbers
• Origin of number series

75
Data Types

• Order Interval
  Origin
• Nominal none - none - none
• Ordinal yes - unequal - none
• Interval yes - equal or unequal -none
• Ratio yes - equal -
  zero

76
Sources of Measurement Differences

• Respondent
• Situational factors
• Measurer or researcher
• Instrument

77
Validity

• Content Validity
• Criterion-Related Validity
• Concurrent
• Predictive
• Construct Validity

78
Reliability

• Stability
• Test-retest
• Equivalence
• Parallel forms
• Internal Consistency
• Split-half
• KR20
• Cronbachs alpha

79
Practicality

• Economy
• Convenience
• Interpretability

80
Chapter 8Scaling Design
81
What is Scaling?

• Assigning numbers to indicants of the properties
  of objects

82
Types of Response Scales

• Rating Scales
• Ranking Scales

83
Types of Rating Scales

• Simple category
• Multiple choice, multiple response
• Likert scale
• Semantic differential

• Numerical
• Multiple fixed rating
• Fixed sum
• Stapel
• Graphic rating

84
Rating Scales Problems to Avoid

• Leniency
• Negative Leniency
• Central Tendency
• Halo Effect

85
Types of Ranking Scales

• Paired-comparison
• Forced Ranking
• Comparative

86
Dimensions of a Scale

• Unidimensional
• Multidimensional

87
Scale Design Techniques

• Arbitrary
• Consensus
• Item Analysis
• Cumulative
• Factor

88
Sampling Design
89
Selection of Elements

• Sampling
• Population Element
• Population
• Census

90
What is a Good Sample?

• Accurate
• Precision of estimate

91
Types of Sampling Designs

• Probability
• Nonprobability

92
Steps in Sampling Design

• What is the relevant population?
• What are the parameters of interest?
• What is the sampling frame?
• What is the type of sample?
• What size sample is needed?
• How much will it cost?

93
Concepts to help understand Probability Sampling

• Standard error of the mean
• Confidence interval
• Central limit theorem

94
Probability Sampling Designs

• Simple Random
• Systemic
• Stratified
• Proportionate
• Cluster
• Double

95
Designing Cluster Samples

• How homogeneous are the clusters?
• Shall we seek equal or unequal clusters?
• How large a cluster shall we take?
• Shall we use a single-stage or multistage
  cluster?
• How large a sample is needed?

96
Nonprobability Sampling

• Reasons to use Nonprobability Sampling instead of
  Probability Sampling
• The nonprobability procedure satisfactorily meets
  the sampling objectives
• Lower cost
• Limited Time
• Not as much human error as selecting a completely
  random sample
• Total list population not available

97
Nonprobability Sampling Designs

• Convenience Sampling
• Purposive Sampling
• Judgement Sampling
• Quota Sampling
• Snowball Sampling

98
Secondary Data Sources
99
Information is Classifies by Two Sources

• Primary Data
• Secondary Data

100
Uses of Secondary Data

• Provides specific reference or citation on some
  point
• Helps decide what further research needs to be
  done
• Justifies bypassing the costs and benefits of
  doing primary research
• May be used as the sole basis for a research study

101
Classifying Secondary Data

• By Source
• By Category
• By Medium
• By Database format

102
Classifying Secondary Data by Source

• Internal
• External

103
Classifying Secondary Data by Category

• Database
• Periodicals
• Government Documents
• Special Collections

104
Classifying Secondary Databy Medium

• Hard copy
• Local-area on-line
• Internet

105
The Librarys Role in Research

• Resources may be acquired through interlibrary
  loans (ILL)
• Certain Databases are available on a local-area
  network (LAN)
• Access to the internet an commercial CD/ DVD-ROM

106
Strategy for Searching for Secondary Data

• Select and analyze a topic
• Explore the topic and state a hypothesis
• Get an overview and retrospective information
• Get more current and specific information
• Get more in-depth information
• Evaluate and close the library research

107
Using Search Engines and Indexes

• The search engine consists of two elements
• Robot/Crawler
• Indexer

108
How to Keep Track of Research?

• Be selective in what you record
• Decide how to record what you will extract from
  the published material
• Develop an orderly recording system

109
Survey Methods Communicating with Respondents
110
Communication Approach Impacts the Research
Process

• Creation and selection of measurement questions
• Sampling issues, drive contact and callback
  procedures
• Instrument design, which incorporates attempts to
  reduce error and create respondent-screening
  procedures
• Data collection procedures and possible
  interviewer training

111
Personal Interview

• Requirements for success
• Availability of the needed information from the
  respondent
• An understanding by the respondent of his or her
  role
• Adequate motivation by the respondent to cooperate

112
Personal Interview

• To Increase Respondents Receptiveness they must
• believe the experience will be pleasant and
  satisfying
• think answering the survey is an important and
  worthwhile use of their time
• have any mental reservations satisfied

113
The Interview

• Introduction
• Establish a good relationship
• Gather the data
• Probing
• Record the Interview

114
Probing Styles

• A brief assertion of understanding and interest
• An expectant pause
• Repeating the question
• Repeating the respondents reply
• A neutral question or comment
• Question clarification

115
Interview Problems

• Non-response error
• Response error
• Interviewer error
• Cost

116
Telephone Interview

• Types
• Computer-assisted telephone interviewing
• Computer-administered telephone survey
• Problems
• Non-contact rate
• Refusal rate

117
Self-Administered

• Types
• Intercept study
• Mail survey
• Disadvantages
• Large non-response error
• Cannot obtain detailed or large amounts of
  information

118
Concurrent Techniques to Improve Mail Response

• Reduce Length
• Survey Sponsorship
• Return Envelopes
• Postage
• Personalization

• Anonymity
• Size, color, and reproduction
• Money Incentives
• Deadline Dates
• Cover Letters

119
Outsourcing Survey Services

• Research Firms Provide
• Centralized-location interviewing
• Focus group facilities
• Trained staff with experience
• Data-processing and statistical analysis
  capabilities
• Access to point of scale data
• Panels

120
Instruments For Respondent Communication
121
3 Phases of the Instrument Design Process

• Developing the instrument design process
• Constructing and refining the measurement
  questions
• Drafting and refining the instrument

122
Developing the Instrument Design Strategy

• You must go through four question levels
• The management question
• Research question
• Investigative questions
• Measurement questions

123
Strategic Concerns of Instrument Design

• What type of data is needed to answer the
  management question
• What communication approach will be used
• Should the question be structured, unstructured,
  or some combination
• Should the question be disguised or undisguised

124
Ways to Interact with the Respondent

• Personal Interview
• Telephone
• Mail
• Computer

125
What are the Three Types of Measurement Questions?

• Target
• Classification
• Administrative

126
4 Questions for Selecting Appropriate Question
Content

• Should this question be asked?
• Is the question of proper scope and coverage?
• Can the respondent adequately answer this
  question, as asked?
• Will the respondent willingly answer this
  question, as asked?

127
How to test a Respondents Knowledge

• Filter Questions
• Screen Questions

128
Question Wording Criteria

• Is the question stated in terms of a shared
  vocabulary?
• Does the question contain vocabulary with a
  single meaning?
• Does the question contain unsupported
  assumptions?
• Is the question correctly personalized?
• Are adequate alternatives presented within the
  question?

129
What Dictates Your Response Strategy?

• Characteristics of respondents
• Nature of the topic being studied
• Type of data needed
• Your analysis plan

130
Types of Response Questions

• Free-response
• Dichotomous
• Multiple choice
• Rating
• Ranking

131
Guidelines to Refining the Instrument

• Awaken the respondents interests
• Use buffer questions as a guide to request
  sensitive information
• Use the funnel approach to move to more specific
  questions

132
Final Step Toward Improving Survey Results

• Pre-testing is an established practice for
  discovering errors and useful for training the
  research team

133
Observational Studies
134
Observation

• Non-behavioral observation
• Record analysis
• Physical condition analysis
• Physical process analysis
• Behavioral observation
• nonverbal analysis
• Linguistic analysis
• Extra-linguistic analysis
• Spatial analysis

135
Advantages of the Observational Method

• Only method available to collect certain types of
  data
• Collect the original data at the time it occurs
• Secure information that participants would ignore
  because its so common it is not seen as relevant

136
Advantages of the Observational Method (cont..)

• Capture the whole event as it occurs in its
  natural environment
• Subjects seem to accept an observational
  intrusion better than they respond to questioning

137
Limitations of the Observational Method

• Observer or recording equipment must be at the
  scene of the event when it takes place
• Slow process
• Expensive process
• Most reliable results are restricted to
  information that can be learned by overt action
  or surface indicators

138
Limitations of the Observational Method (cont..)

• Research environment is more likely suited to
  subjective assessment and recording of data than
  to quantification of events
• Limited as a way to learn about the past
• Cannot observe rationale for actions, only
  actions themselves

139
Relationship between observer and subject

• Direct or indirect observation
• Observers presence known or unknown to the
  subject
• Observers involvement level with the respondent

140
Observation

• Direct
• Indirect
• Participant
• Simple
• Systematic

141
Guidelines for selecting observers

• Ability to concentrate in a setting full of
  distractions
• Ability to remember details of an experience
• Ability to be unobtrusive in the observational
  situation

142
Data collection

• Who?
• What?
• Event Sampling
• Time Sampling
• When?
• How?

143
Experimentation
144
Types of variables in Experiments

• Independent Variables
• Dependent Variables

145
What are the Advantages of an Experiment?

• Researchers ability to manipulate the
  independent variable
• Contamination from extraneous variables can be
  controlled more efficiently
• Convenience and cost
• Replication

146
What are the Disadvantages?

• Artificiality of the laboratory
• Generalization from non-probability samples
• Larger budgets needed
• Restricted to problems of the present or
  immediate future
• Ethical limits to manipulation of people

147
How to Conduct an Experiment?

• Select relevant variables
• Specify the treatment levels
• Control the experimental environment
• Choose the experimental design
• Select and assign the subjects
• Pilot-test, revise, and test
• Analyze the data

148
Ways to Assign Subjects?

• Random Assignment
• Matching Assignment
• Quota Matrix

149
Does a Measure Accomplish What it Claims?

• Internal validity
• External validity

150
Variations in Experimental Designs

• Pre-experimental designs
• True experimental designs
• Field experiments

151
Types of Pre-experimental Designs?

• One-shot case study
• One-group pretest-posttest design
• Static group comparison

152
Types of True Experimental Designs

• Pretest-posttest control group design
• Posttest only control group design

153
Operational Extensions of True Designs

• Completely randomized designs
• Randomized block design
• Latin square
• Factorial design
• Covariance analysis

154
What are Field ExperimentsQuasi or Semi?

• Non equivalent control group design
• Separate sample pretest-posttest design
• Group time series design

155
Data preparation and Preliminary Analysis
156
Editing

• Detects errors and omissions, corrects them when
  possible, and certifies that minimum data quality
  standards are achieved

157
Editing (cont..)

• Guarantees that data are
• accurate
• consistent with other information
• uniformly entered
• complete
• arranged to simplify coding and tabulation

158
Coding

• Rules that guide the establishment of category
  sets
• Appropriate to the research problem and purpose
• Exhaustive
• Mutually exclusive
• Derived from one classification principal

159
Content Analysis

• Follows a systematic process with the selection
  of a unitization scheme
• Syntactical unit
• Referential unit
• Propositional unit
• Thematic unit

160
Data Entry Options

• Optical Scanning
• Spreadsheets
• Data warehouse
• Transformation and cleaning
• End-user access tools
• Data marts

161
Descriptive Statistics

• Distribution
• Standard normal distribution
• Central tendency
• Mean
• Median
• Mode
• Variability

• Variance
• Standard deviation
• Range
• Interquartile range
• Skewness
• Kurtosis

162
Techniques to Display and Examine Distributions

• Frequency table
• Histograms
• Display all intervals in a distribution, even
  without observed values
• Examine the shape of the distribution for
  Skewness, kurtosis, and the modal pattern
• Stem and leaf display

163
Techniques (cont.)

• Box and whisker-plot
• Rectangular plot tat encompasses 50 of the data
  values
• A center line marking the median and going go
  through the width of the box
• The edges of the box (hinges)
• Whiskers that extend from the right and left
  hinges to the largest and smallest values

164
Techniques (cont.)

• Transformation
• To improve interpretation and compatibility with
  other data sets
• To enhance symmetry and stabilize spread
• To improve linear relationships between and among
  variables

165
Data Mining Techniques

• Data visualization
• Dimensions
• Measurements
• Hierarchies
• Clustering
• Neural networks
• Tree Models
• Classification

166
Data Mining Techniques (cont.)

• Market-Basket Analysis
• Sequence Based Analysis
• Fuzzy Logic
• Genetic Algorithms
• Fractal-base Transformation

167
Data Mining Process

• Sample
• Explore
• Modify
• Model
• Assess

168
Hypothesis Testing
169
Two Approaches to Hypothesis Testing

• Classical Statistics
• Bayesian Statistics

170
Types of Hypotheses

• Null
• Alternative

171
The Logic of HypothesisTesting

• Two tailed test
• One tailed test

172
Decision Errors in Testing

• Type I error
• Type II error

173
Testing for Statistical Significance

• State the null hypothesis
• Choose the statistical test
• Select the desired level of significance
• Compute the calculated difference value
• Obtain the critical value
• Make the decision

174
What are Significant Tests?

• Parametric tests
• Non-parametric tests

175
How to Test the Null Hypothesis

• Analysis of variance (ANOVA)

176
How to select a test

• Does the test involve one sample, two samples, or
  k samples?
• If two samples or k samples are involved, are the
  individual cases independent or related?
• Is the measurement scale nominal, ordinal,
  interval, or ratio?

177
When to use the K Related Sample Tests

• The grouping factor has more than two levels
• Observations or subjects are matched or the same
  subject is measured more than once
• The data are at least interval

178
Measures of Association
179
Bivariate Correlation vs.. Non-parametric
Measures of Association

• Parametric correlation requires two continuous
  variables measured on an interval or ratio scale
• The coefficient does not distinguish between
  independent and dependent variables

180
Bivariate Correlation Analysis

• Pearson correlation coefficient
• r symbolized the coefficients estimate of linear
  association based on sampling data
• Correlation Coefficients reveal the magnitude and
  direction of relationships
• Coefficients sign ( or -) signifies the
  direction of the relationship
• Assumptions of r
• Linearity
• Bivariate normal distribution

181
Bivariate Correlation Analysis

• Scatterplots
• Provide a means for visual inspection of data
• Both direction and shape of a relationship are
  conveyed

182
Interpretation of Coefficients

• Coefficient of determination
• Correlation matrix
• used to display coefficients for more than two
  variables
• Correlation coefficient does not imply causation

183
Interpretation of Coefficients

• Suggests alternate explanations for correlation
  results
• X causes Y, or Y causes X, or XY are activated
  by one or more other variables, or XY influence
  each other reciprocally
• Practical Significance
• Statistical Significance
• Artifact correlations

184
Bivariate Linear Regression

• Used to make simple and multiple predictions
• Regression coefficients
• Slope
• Intercept
• Error term
• Method of least squares

185
Interpreting Linear Regression

• Residuals
• Prediction and confidence bands

186
Interpreting Linear Regression

• Goodness of fit
• Zero slopes come from
• Y completely unrelated to X and no systematic
  pattern is evident
• Constant values of Y for every value of X
• data are related, but represented by a nonlinear
  function
• Tests
• t test
• F test
• Coefficient of Determination

187
Non-parametric Measures of Association

• Measures for nominal data
• When there is no relationship at all, coefficient
  should be 0
• When there is a complete dependency, the
  coefficient should display unity or 1

188
Non-parametric Measures of Association

• Chi-square based measure
• Phi
• Cramers V
• Contingency coefficient of C
• Proportional reduction in error (PRE)
• Lambda
• Tau

189
Characteristics of Ordinal Data

• Concordant- subject ranks higher on one variable
  also ranks higher on the other variable
• Discordant- subject ranks higher on one variable
  is ranked lower on the other variable

190
Measures for Ordinal Data

• Gamma
• Somers d
• Spearmans rho
• Kendalls tau b
• Kendalls tau c
• No assumption of bivariate normal distribution
• Values range from 1.0 to -1.0

191
Multivariate AnalysisAn Overview
192
Selecting a Multivariate Technique

• Dependency
• Interdependency

193
What are Dependency Techniques?

• Multiple regression
• Discriminant analysis
• Multivariate analysis if variance, or MANOVA
• Linear structural relationships, or LISREL
• Conjoint analysis

194
What are Interdependency Techniques?

• Factor analysis
• Cluster analysis
• Multidimensional scaling (MDS)

195
Use Multiple Regression as a Descriptive Tool

• Predict values for a criterion variable by
  developing a self-weighting estimating equation
• Control for confounding variables to better
  evaluate the contribution other variables
• Test and explain causal theories

196
Uses for Discriminant Analysis

• Classify persons or objects into various groups
• Analyze known groups to determine the relative
  influence of specific factors

197
Why Use MANOVA?

• In business research, MANOVA can be used to test
  differences among samples of employees,
  customers, manufactured items, and production
  parts.

198
The Two Models of LISREL

• Measurement
• Structural equation

199
Applications for Conjoint Analysis

• Market Research
• Product development

200
What is Factor Analysis?

• Computational techniques that reduce variables to
  a manageable number
• Measurement statistics

201
Five Basic Steps to the Application of Cluster
Studies

• Selection of the sample to be clustered
• Definition of the variables on which to measure
  the objects, events, or people
• computation of similarities among the entities
  through correlation, Euclidean distances, and
  other techniques
• Selection of mutually exclusive clusters
• Cluster comparison and validation

202
What does Multidimensional Scaling Do?

• Creates a special description of a respondents
  perception about a product, service, or other
  object of interest

203
Written and Oral Reports
204
Written Research Report

• Short report
• Tell the reader why you are writing
• If in response, remind reader the exact point,
  answer it, and follow with details
• Write in expository style with brevity and
  directness
• Write report today and leave it for tomorrow to
  review before sending it
• Attach detailed material as appendices when needed

205
Written Research Report

• Long report
• Technical report
• Management report

206
Research Report Components

• Methodology
• Sampling design
• Research design
• Data collection
• Data analysis
• Limitations
• Conclusions
• Summary and conclusions
• Recommendations
• Appendices
• Bibliography

• Prefatory Items
• Letter of transmittal
• Title page
• Authorization letter
• Executive summary
• Table of contents
• Introduction
• Problem Statement
• Research objectives
• Background

207
Written Report Considerations

• Order
• Sentence outline
• Topic outline
• Readability indices
• Pace
• Tone

208
Presentation of Statistics

• Text paragraph
• Semi-tabular form
• Tables
• Graphics

209
Graphics

• Line graphs
• Area charts
• Pie charts
• Bar charts
• Pictograph
• 3-D graphics

• Control charts
• Outliners- observations that fall outside the
  control lines
• Runs- data points in a series above or below the
  central line
• Pareto diagram

210
Oral Presentations

• Preparation
• Length
• Content
• Opening
• Findings and conclusions
• Recommendations
• Outline
• Delivery
• Vocal Characteristics
• Physical Characteristics

211
Audiovisuals

• Chalkboard and whiteboards
• Handout material
• Flip charts
• Overhead transparencies
• Slides
• Computer drawn visuals
• Computer animation