Part 1 Introduction to Business Research.

Part 1 Introduction to Business Research

Donald Cooper Pamela Schindler
Chapter 1 Business Research Methods Donald Cooper Pamela Schindler

Chapter 1 Research in Business

Why Study Research? Slide 1 - 1 Research provides you with the knowledge and skills needed for the fast-paced decision-making environment

Why Managers need Better Information
Slide 1 - 2 Global and domestic competition is more vigorous Organizations are increasingly practicing data mining and data warehousing

The Value of Acquiring Skills
Slide 1 - 3 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

Types of Studies Used to do Research
Slide 1 - 4 Reporting Descriptive Explanatory Predictive

Different Styles of Research
Slide 1 - 5 Applied Research Pure Research/Basic Research Business Research

What is Good Research? Slide 1 - 6 Following the standards of the scientific method Purpose clearly defined Research process detailed Research design thoroughly planned High ethical standards applied Limitations frankly revealed

What is Good Research? Slide 1 - 7 Following the standards of the scientific method (cont.) Adequate analysis for decision-maker’s needs Findings presented unambiguously Conclusions justified Researcher’s experience reflected

The Manager-Researcher Relationship
Slide 1 - 8 Manager’s obligations Specify problems Provide adequate background information Access to company information gatekeepers Researcher’s obligations Develop a creative research design Provide answers to important business questions

Manager-Researcher Conflicts
Slide 1 - 9 Management’s limited exposure to research Manager sees researcher as threat to personal status Researcher has to consider corporate culture and political situations Researcher’s isolation from managers

Business Research Methods
Donald Cooper Pamela Schindler

Addressing Management Problems with Scientific Thinking

Sources of Knowledge Slide 2 - 1 Empiricists attempt to describe, explain, and make predictions through observation Rationalists believe all knowledge can be 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

The Essential Tenets of Science
Slide 2 - 2 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

Ways to Communicate Exposition Argument
Slide 2 - 3 Exposition descriptive statements that merely state and do not give reason Argument allows us to explain, interpret, defend, challenge, and explore meaning

Important Arguments in Research
Slide 2 - 4 Deduction is a form of inference that purports to be conclusive Induction draws conclusions from one or more particular facts

The Building Blocks of Theory
Slide 2 - 5 Concepts Constructs Definitions Variables Propositions and Hypotheses Theories Models

Understanding Concepts
A concept is a bundle of meanings or characteristics associated with certain events, objects, conditions, situations, and behaviors Concepts have been developed over time through shared usage Slide 2 - 6

Understanding Concepts
The success of research hinges on: how clearly we conceptualize how well others understand the concepts we use Slide 2 - 7

What is a Construct? Slide 2 - 8 An image or idea specifically invented for a given research and/or theory-building purpose

Types of Variables Independent Dependent Moderating Extraneous
Slide 2 - 9 Independent Dependent Moderating Extraneous Intervening

The Role of the Hypothesis
Slide Guides the direction of the study Identifies facts that are relevant Suggests which form of research design is appropriate Provides a framework for organizing the conclusions that result

What is a Good Hypothesis?
Slide A good hypothesis should fulfill three conditions: Must be adequate for its purpose Must be testable Must be better than its rivals

The Value of a Theory Narrows the range of facts we need to study
Slide Narrows the range of facts we need to study Suggests which research approaches will yield the greatest meaning Summarizes what is known about an object of study Predicts further facts that should be found

Business Research Methods Donald Cooper Pamela Schindler Irwin/McGraw-Hill

The Research Process

The Management-Research Question Hierarchy
Slide 3 - 1 Management Dilemma Measurement Questions Investigative Questions Research Questions Management Questions Management Decision 1 2 3 4 5 6

Working with the Hierarchy
Slide 3 - 2 Management Dilemma The symptom of an actual problem Not difficult to identify a dilemma, however choosing one to focus on may be difficult

Slide 3 - 3 Management Question Categories Choice of purposes or objective Generation and evaluation of solutions Troubleshooting or control situation

Slide 3 - 4 Fine tune the research question Examine concepts and constructs Break research questions into specific second-and-third-level questions Verify hypotheses with quality tests Determine what evidence answers the various questions and hypothesis Set the scope of your study

Slide 3 - 5 Investigative Questions Questions the researcher must answer to satisfactorily arrive at a conclusion about the research question

Slide 3 - 6 Measurement Questions The questions we actually ask or extract from respondents

Other Processes in the Hierarchy
Slide 3 - 7 Exploration Recent developments Predictions by informed figures about the prospects of the technology Identification of those involved in the area Accounts of successful ventures and failures by others in the field

Research Process Problems
Slide 3 - 8 The Favored Technique Syndrome Company Database Strip-Mining Unresearchable Questions Ill-Defined Management Problems Politically Motivated Research

Designing the Study Slide 3 - 9 Select a research design from the large variety of methods, techniques, procedures, protocols, and sampling plans

Resource Allocation & Budgets
Slide Guides to plan a budget Project planning Data gathering Analysis, interpretation, and reporting Types of budgeting Rule-of-thumb Departmental or functional area Task

Evaluation Methods Ex Post Facto Evaluation Prior Evaluation
Slide Ex Post Facto Evaluation Prior Evaluation Option Analysis Decision Theory

Contents of a Research Proposal
Slide Statement of the research question Brief description of research methodology Pilot Testing Data collection Data preparation Data analysis and interpretation Research reporting

Data Collection Characterized by Types abstractness verifiability
Slide Characterized by abstractness verifiability elusiveness closeness to the phenomenon Types Secondary data Primary data

Final Steps in Research
Slide Data analysis Reporting the results Executive summary Overview of the research Implementation strategies for the recommendations Technical appendix

Business Research Methods Donald Cooper Pamela Schindler

The Research Proposal

Purpose of the Research Proposal
Slide 4 - 1 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

The Research Sponsor Slide 4 - 2 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

What are the Benefits of the Proposal to a Researcher?
Slide 4 - 3 Allows the researcher to plan and review the project’s steps Serves as a guide throughout the investigation Forces time and budget estimates

Types of Research Proposals
Slide 4 - 4 Internal External

Proposal Complexity 3 levels of complexity:
Slide 4 - 5 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

How to Structure the Research Proposal?
Slide 4 - 6 Create proposal modules Put together various modules to tailor your proposal to the intended audience

Modules in a Research Proposal
Slide 4 - 7 Executive Summary Problem Statement Research Objectives Literature Review 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 Appendices

What to include in the Appendices?
Slide 4 - 8 A glossary of concepts, constructs, and definitions Samples of the measurement instrument Other materials that reinforce the body of the proposal

Evaluating the Research Proposal
4-10 Evaluating the Research Proposal Slide 4 - 9 Proposal must be neatly written in appropriate writing style Major topics 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

Business Research Methods Donald Cooper Pamela Schindler Irwin/McGraw-Hill

Ethics in Business Research

What are Research Ethics?
Slide 5 - 1 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

Ethical Treatment of Respondents and Subjects
Slide 5 - 2 Begin data collection by explaining to the respondent the benefits expected from the research Explain to the respondents that their rights and well-being will be adequately protected, and say how this will be done Be certain that interviewers obtain the informed consent of the respondent

Deception Slide 5 - 3 The respondent is told only part of the truth or when the truth is fully compromised To prevent biasing the respondents before the survey or experiment To protect the confidentiality of a third party

Issues Related to Protecting Respondents
Slide 5 - 4 Informed consent Debriefing Right to Privacy/Confidentiality Data Collection in Cyberspace

Ethical Issues related to the Client
Slide 5 - 5 Sponsor non-disclosure Purpose non-disclosure Findings non-disclosure Right to quality research

Ethics Related to Sponsor
Sometimes researchers will be asked by sponsors to participate in unethical behavior. To avoid coercion by sponsor the researcher should: Educate sponsor to the purpose of research Explain researcher’s role Explain how distortion of the truth leads to future problems If necessary, terminate relationship with sponsor Slide 5 - 6

Ethical Issues related to Researchers and Team Members
Slide 5 - 7 Safety Ethical behavior of assistants Protection of anonymity

Part 2 The Design of Research

Chapter 6 Design Strategies

What is Research Design?
Slide 6 - 1 A plan for selecting the sources and types of information used to answer research questions A framework for specifying the relationships among the study variables A blueprint that outlines each procedure from the hypothesis to the analysis

Classifications of Designs
Slide 6 - 2 Exploratory study is usually to develop hypotheses or questions for further research Formal study is to test the hypotheses or answer the research questions posed

Methods of Data Collection
Slide 6 - 3 Monitoring, which includes observational studies Interrogation/communication study

Power to Produce Effects
Slide 6 - 4 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

Purpose of the Study Slide 6 - 5 Descriptive tries to explain relationships among variables Causal study is how one variable produces changes in another

The Time Dimension Slide 6 - 6 Cross-sectional studies are carried out once and represent a snapshot of one point in time Longitudinal studies are repeated over an extended period

The Topical Scope Slide 6 - 7 Statistical studies attempt to capture a population’s characteristics by making inferences from a sample’s characteristics Case studies place more emphasis on a full contextual analysis of fewer events or conditions and their interrelations

The Research Environment
Slide 6 - 8 Field conditions Laboratory conditions Simulations

A Subjects’ Perceptions
Slide 6 - 9 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

Why do Exploratory Studies?
Slide Exploration is particularly useful when researchers lack a clear idea of the problems

Data Collection Techniques
Slide Qualitative techniques Secondary data Focus groups Two-stage design

Causation The essential element of causation is A “produces” B or
Slide The essential element of causation is A “produces” B or A “forces” B to occur

Causal Study Relationships
Slide Symmetrical Reciprocal Asymmetrical

Asymmetrical Relationships
Slide Stimulus-Response Property-Disposition Disposition-Behavior Property-Behavior

Achieving the Ideal Experimental Design
Slide Control Random Assignment Matching Randomization Manipulation and control of variables

Chapter 8 Measurement

Measurement Selecting observable empirical events
Slide 8 - 1 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

What is Measured? Objects: Things of ordinary experience
Slide 8 - 2 Objects: Things of ordinary experience Some things not concrete Properties: characteristics of objects

Characteristics of Data
7-4 Characteristics of Data Slide 8 - 3 Classification Order Distance (interval between numbers) Origin of number series

Data Types Order Interval Origin Nominal none none none
Slide 8 - 4 Order Interval Origin Nominal none none none Ordinal yes unequal none Interval yes equal or none unequal Ratio yes equal zero

Sources of Measurement Differences
Slide 8 - 5 Respondent Situational factors Measurer or researcher Data collection instrument

Validity Content Validity Criterion-Related Validity
Slide 8 - 6 Content Validity Criterion-Related Validity Predictive Concurrent Construct Validity

Reliability Stability Equivalence Internal Consistency Test-retest
Slide 8 - 7 Stability Test-retest Equivalence Parallel forms Internal Consistency Split-half KR20 Cronbach’s alpha

7-9 Practicality Slide 8 - 8 Economy Convenience Interpretability

Chapter 9 Business Research Methods Donald Cooper Pamela Schindler Irwin/McGraw-Hill

Chapter 9 Measurement Scales

What is Scaling? Slide Assigning numbers to indicants of the properties of objects

Types of Response Scales
Slide 9 - 2 Rating Scales Ranking Scales Categorization

Types of Rating Scales Simple category
Slide 9 - 3 Simple category Multiple choice, single response Multiple choice, multiple response Likert scale Semantic differential Numerical Multiple rating Fixed sum Stapel Graphic rating

Rating Scale Errors to Avoid
Slide 9 - 4 Leniency Negative Leniency Positive Leniency Central Tendency Halo Effect

Types of Ranking Scales
Slide 9 - 5 Paired-comparison Forced Ranking Comparative

Dimensions of a Scale Slide 9 - 6 Unidimensional Multidimensional

Scale Design Techniques
Slide 9 - 7 Arbitrary Consensus Item Analysis Cumulative Factor

Sources and Collection of Data
Chapter 10 Sources and Collection of Data

Exploratory Research Expand understanding of management dilemma
Slide Expand understanding of management dilemma Expand understanding of research question Identify plausible investigative questions

Levels of Information Primary sources Secondary sources
Slide Primary sources Secondary sources Tertiary sources

Types of Information Sources
Slide Indexes and Bibliographies Dictionaries Encyclopedias Handbooks Directories

Secondary Sources by Type
Slide Indexes and Bibliographies to find or locate books or articles to find authors, topics to use in online searches

Slide Dictionaries to identify jargon of an industry--used for online searches to identify bell-weather events in an industry to identify knowledgeable people to interview to identify organizations of influence

Slide Encyclopedias To identify historical or background information To find critical dates within an industry To find events of significance to the industry, company

Slide Handbooks To find facts relevant to topic To identify influential individuals through source citations

Slide Directories To identify influential people and organizations to find addresses, , other contact info on these people and organizations

Evaluating Information Sources
Slide Purpose Scope Authority Audience Format

Evaluating Sources Purpose what the author is attempting to accomplish
Slide Purpose what the author is attempting to accomplish identify hidden agenda(s) identify direction of bias Seek both biased and unbiased sources

Evaluating Sources Scope Identify dates of inclusion and exclusion
Slide Scope Identify dates of inclusion and exclusion Identify subjects of inclusion and exclusion

Evaluating Sources Authority Identify background of author
Slide Authority Identify background of author Credentials: educational, professional Experience: duration, setting, level Identify the level of scholarship in content footnotes, endnotes

Evaluating Sources Audience Identify knowledge level and background
Slide Audience Identify knowledge level and background Identify orientation and bias Seek biased and unbiased sources

Evaluating Sources Format Order of content Versatility of use Indexed?
Slide Format Order of content Versatility of use Indexed? Searchable? Downloadable?

Searching Databases Select an appropriate database ABI/Inform
Slide Select an appropriate database ABI/Inform Business InfoSuite Business Source DowJones Interactive Nexis-Lexis Universe

Searching Databases Select an appropriate database
Slide Select an appropriate database Construct a search query

Searching Databases Construct a search query Boolean Operators
OR - for plurals, synonyms spelling variations woman OR women AND - narrows your search advertising AND bibliography NOT/AND NOT- eliminates terms award NOT trophy ADJ - order key terms within your search assisted ADJ living Slide

Searching Databases Construct a search query Boolean Operators
Slide Construct a search query Boolean Operators ? or * - to truncate a term nur* for nurse, nursing “X” for phrase searching “advertising campaigns” Limiters dates source type language

Searching Databases Select an appropriate database
Slide Select an appropriate database Construct a search query Review and evaluate search results Relevancy Quantity Timeliness

Searching Databases Modify the search query Check bibliography
Slide Modify the search query Check bibliography new key words, other authors Link directly Adapt original search query Create new search query with new key words Search for other works by same author(s)

Searching Databases Modify the search query Document findings
Slide Modify the search query Document findings Print or download search findings Download full-text source Print full-text source

Searching Databases Modify the search query Document findings
Slide Modify the search query Document findings Retrieve or request articles Search online catalog Interlibrary loan Interlibrary delivery

Web Searches Define your question Select Search Engine or Directory
Danny Sullivan’s Search Engine Watch Greg Notess” Search Engine Showdown Slide

Web Searches Determine Search Options and Protocol
Slide Determine Search Options and Protocol Construct search query Review search results

Web Searches Modify search query and search again
Slide Modify search query and search again Search using a different search engine Document your findings search findings full text sources Supplement web results from other sources

Specific Web Searches Slide Known-Item Who Where What

Government Sources Government organizations
Slide Government organizations Laws, regulations, court decisions Government statistics

Mining Internal Sources
Slide Data warehouse Data mart Data mining Pattern discovery Predicting trends and behaviors

Data Mining Techniques
Slide Data Visualization Dimensions Measurements Hierarchies Clustering Neural Networks Tree Models Classification

Data Mining Techniques (cont.)
Slide Estimation Association Market-Basket Analysis Sequence Based Analysis Fuzzy Logic Genetic Algorithms Fractal-Based Transformation

Data Mining Process Slide Sample Explore Modify Model Assess

Survey Methods: Communicating with Respondents
Chapter 11 Survey Methods: Communicating with Respondents

Communication Approach Impacts the Research Process
Slide 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 processes, which create the need for follow-up procedures and possible interviewer training

Personal Interview Requirements for success
Slide 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

Personal Interview To Increase Respondent’s Receptiveness they must
Slide To Increase Respondent’s 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

The Interview Introduction Gather the data Record the interview
Slide Introduction Establish a good relationship Gather the data Probing Record the interview

Probing Styles A brief assertion of understanding and interest
Slide A brief assertion of understanding and interest An expectant pause Repeating the question Repeating the respondent’s reply A neutral question or comment Question clarification

Interview Problems Nonresponse error Response error Interviewer error
Slide Nonresponse error Response error Interviewer error Cost

Telephone Interview Types Problems
Slide Types Computer-assisted telephone interviewing Computer-administered telephone survey Problems Noncontact rate Refusal rate

Self-Administered Surveys
Slide Types Mail survey Computer-delivered Intercept studies Disadvantages Large nonresponse error Cannot obtain detailed or large amounts of information

Concurrent Techniques to Improve Mail Response
Slide Reduce Length Survey Sponsorship Return Envelopes Postage Personalization Anonymity Size, Color, and Reproduction Money Incentives Deadline Dates Cover Letters

Outsourcing Survey Services
Slide Research Firms Provide Centralized-location interviewing Focus group facilities Trained staff with experience Data-processing and statistical analysis capabilities Access to point-of-sale data Panels

Instruments for Respondent Communication
Chapter 12 Instruments for Respondent Communication

Instrument Design Process
Slide Phase 1: Developing the instrument design strategy Phase 2: Constructing and refining the measurement questions Phase 3: Drafting and refining the instrument

Developing the Instrument Design Strategy
Slide Management-Research Question Hierarchy: The management problem/question Research question(s) Investigative questions Measurement questions

Strategic Concerns of Instrument Design
Slide What type of data is needed to answer the management question? What communication approach will be used? Should the questions be structured, unstructured, or some combination? Should the questions be disguised or undisguised?

Ways to Interact with the Respondent
Slide Personal interview Telephone Mail Computer

Types of Measurement Questions?
Slide Target Classification Administrative

Appropriate Question Content
Slide 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?

How to Test a Respondent’s Appropriateness
Slide Filter questions Screen questions

Question Wording Criteria
Slide 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?

What Dictates Your Response Strategy?
Slide Characteristics of respondents Nature of the topic(s) being studied Type of data needed Your analysis plan

Types of Response Questions
Slide Free-response Dichotomous Multiple-choice Checklist Rating Ranking

Guidelines to Refining the Instrument
Slide Awaken the respondent's interest Use buffer questions as a guide to request sensitive information Use the funnel approach to move to more specific questions

Improving Survey Results
Slide Pretesting is an established practice for discovering errors and useful for training the research team

Observational Studies
Chapter 13 Observational Studies

Observation Nonbehavioral observation Behavioral observation
Slide Nonbehavioral observation Behavioral observation

Observation Nonbehavioral observation Record analysis
Slide Nonbehavioral observation Record analysis Physical condition analysis Process or activity analysis

Observation Behavioral observation Nonverbal analysis
Slide Behavioral observation Nonverbal analysis Linguistic analysis Extralinguistic analysis Spatial analysis

Advantages of the Observational Method
Slide Collect the original data at the time it occurs Secure information that participants would ignore because it’s so common it is not seen as relevant Only method available to collect certain types of data

Advantages of the Observational Method (cont.)
Slide Capture the whole event as it occurs in its natural environment Subjects seem to accept an observational intrusion better than they respond to questioning

Limitations of the Observational Method
Slide 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

Limitations of the Observational Method (cont.)
Slide 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

Relationship between Observer and Subject
Slide Direct or indirect observation Observer’s presence known or unknown to the subject Observer is involved or not involved with the respondent

Observation Methods Direct Indirect Participant Simple Systematic
Slide Direct Indirect Participant Simple Systematic

Guidelines for Selecting Observers
Slide Ability to concentrate in a setting full of distractions Ability to remember details of an experience Ability to be unobtrusive in the observational situation Ability to extract the most from an observational study

Observation Data Collection
Slide Who What Event Sampling Time Sampling When How Where

Chapter 14 Experimentation

Variables in Experiments
Slide Independent variables Dependent variables

Advantages of an Experiment?
Slide Researcher’s ability to manipulate the independent variable Contamination from extraneous variables can be controlled more efficiently Convenience Cost Replication

Disadvantages of Experiments
Slide Artificiality of the laboratory Generalization from nonprobability samples Larger budgets needed Restricted to problems of the present or immediate future Ethical limits to manipulation of people

Experimentation Process
Slide 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

Ways to Assign Subjects
Slide Random Assignment Matching Assignment Quota matrix

Does a Measure Accomplish What it Claims?
Slide Internal validity External validity

Threats to Internal Validity
Slide History Maturation Testing Instrumentation Selection Statistical Regression Experimental Mortality

Threats to External Validity
Slide The Reactivity of Testing on X Interaction of Selection and X Other Biasing Effects on X Artificial setting of testing Respondents knowledge of testing

Experimental Designs Preexperimental designs True experimental designs
Slide Preexperimental designs True experimental designs Field experiments

Design Symbols Slide X the introduction of an experimental stimulus to the respondent 0 a measure or observation activity R an indication that sample units have been randomly assigned

Preexperimental Designs
Slide One-shot case study One-group pretest-posttest design Static group comparison

True Experimental Designs
Slide Pretest-posttest control group design Posttest-only control group design

Operational Extensions of True Designs
Slide Completely randomized designs Randomized block design Latin square Factorial design Covariance analysis

Field Experiments: Quasi- or Semi-Experiments
Slide Non Equivalent Control Group Design Separate Sample Pretest-Posttest Design Group Time Series Design

Analysis and Presentation of Data
Part 4 Analysis and Presentation of Data

Data Preparation and Description
Chapter 15 Data Preparation and Description

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

Editing (cont.) Guarantees that data are accurate
Slide Guarantees that data are accurate consistent with other information uniformly entered complete arranged to simplify coding and tabulation

Editing Field Editing Central Editing
Slide Field Editing translation of ad hoc abbreviations and symbols used during data collection validation of the field results. Central Editing

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

Content Analysis for Coding
Slide Measures the semantic content of a message Researches the objective, systematic, and quantitative description of the content of a communication Syntactical unit Referential unit Propositional unit Thematic unit

Data Entry Options Optical scanning Voice recognition Keyboard
Slide Optical scanning Voice recognition Keyboard

Data Entry Formats Database with full screen editor Spreadsheet
Slide Database with full screen editor Spreadsheet

Descriptive Statistics
Slide 15 -8 Distribution Descriptors Location Central Tendency Mean Median Mode

Slide 15 -9 Distribution Descriptors Spread Variance, Standard Deviation, Range, Interquartile Range

Slide Distribution Descriptors Shape Skewness Kurtosis

Exploring, Displaying, & Examining Data
Chapter 16 Exploring, Displaying, & Examining Data

Types of Data Analysis Exploratory data analysis
Slide Exploratory data analysis the data guide the choice of analysis--or a revision of the planned analysis Confirmatory data analysis closer to classical statistical inference in its use of significance and confidence may use information from a closely related data set or by validating findings through the gathering and analyzing of new data

Techniques to Display and Examine Distributions
Slide Frequency Table Visual Displays Histograms Stem-and-leaf display Box-plot Crosstabulation of Variables

Techniques to Display and Examine Distributions
Slide Histograms Display all intervals in a distribution, even without observed values Examine the shape of the distribution for skewness, kurtosis, and the modal pattern

Techniques (cont.) Box-plot (box and whisker-plot)
Slide Box-plot (box and whisker-plot) Rectangular plot encompasses 50% of the data values Edges of the box (hinges) Center line through the width of the box marks the median Whiskers extend from the right and left hinges to the largest and smallest values

Techniques (cont.) Transformation
Slide Transformation To improve interpretation and compatibility with other data sets To enhance symmetry and stabilize spread To improve linear relationships between and among variables

Improvement & Control Analysis
Slide Statistical process control Uses statistical tools to analyze, monitor, and improve process performance Total Quality Management Control chart Displays sequential measurements of a process together with a center line and control limits Upper control limit Lower control limit

Types of Control Charts
Slide Variables data (ratio or interval measurements) X-bar R-charts s-charts Pareto Diagrams Bar chart whose percentages sum to 100 percent

Geographic Information Systems
Slide Systems of hardware, software, and procedures that capture, store, manipulate, integrate, and display spatially-referenced data

Geographic Information Systems
Slide Minimum four components Integrating information from various sources Capturing data Projection and restructuring Modeling

Crosstabulation A technique for comparing two classification variables
Slide A technique for comparing two classification variables Cells Marginals Contingency tables

Percentaging Errors Averaging percentages without weighting
Slide Averaging percentages without weighting Using too-large percentages (>100%) Using percentage with very small sample Citing percentage decrease exceeding 100 percent

Other Table-based Analysis
Slide Automatic Interaction Detection (AID) Sequential partitioning procedure that uses a dependent variable and set of predictors Searches among up to 300 variables for the best single division of data into subsets according to each predictor variable, Chooses one division approach splits the sample using chi-square tests to create multi-way splits.

Chapter 17 Hypothesis Testing

Approaches to Hypothesis Testing
Slide Classical Statistics sampling-theory approach objective view of probability decision making rests on analysis of available sampling data Bayesian Statistics extension of classical statistics consider all other available information

Types of Hypotheses Null Alternative
Slide Null that no statistically significant difference exists between the parameter and the statistic being compared Alternative logical opposite of the null hypothesis that a statistically significant difference does exist between the parameter and the statistic being compared.

Logic of Hypothesis Testing
Slide Two tailed test nondirectional test considers two possibilities One tailed test directional test places entire probability of an unlikely outcome to the tail specified by the alternative hypothesis

Decision Errors in Testing
Slide Type I error a true null hypothesis is rejected Type II error one fails to reject a false null hypothesis

Testing for Statistical Significance
Slide State the null hypothesis Choose the statistical test Select the desired level of significance Compute the calculated difference value Obtain the critical value Interpret the test

Classes of Significance Tests
Slide Parametric tests Z or t test is used to determine the statistical significance between a sample distribution mean and a population parameter Assumptions: independent observations normal distributions populations have equal variances at least interval data measurement scale

Classes of Significance Tests
Slide Nonparametric tests Chi-square test is used for situations in which a test for differences between samples is required Assumptions independent observations for some tests only normal distribution not necessary homogeneity of variance not necessary appropriate for nominal and ordinal data, may be used for interval or ratio data

How to Test the Null Hypothesis
Slide Analysis of variance (ANOVA) the statistical method for testing the null hypothesis that means of several populations are equal

Multiple Comparison Tests
Slide Multiple comparison procedures test the difference between each pair of means and indicate significantly different group means at a specified alpha level (<.05) use group means and incorporate the MSerror term of the F ratio

How to Select a Test Which does the test involve? one sample,
Slide Which does the test involve? one sample, two samples k samples If two or k samples,are the individual cases independent or related? Is the measurement scale nominal, ordinal, interval, or ratio?

K Related Samples Test Use when:
Slide Use when: The grouping factor has more than two levels Observations or subjects are matched or the same subject is measured more than once Interval or ratio data

Measures of Association
Chapter 18 Measures of Association

Bivariate Correlation vs. Nonparametric Measures of Association
Slide Parametric correlation requires two continuous variables measured on an interval or ratio scale The coefficient does not distinguish between independent and dependent variables

Bivariate Correlation Analysis
Pearson correlation coefficient r symbolized the coefficient's estimate of linear association based on sampling data Correlation coefficients reveal the magnitude and direction of relationships Coefficient’s sign (+ or -) signifies the direction of the relationship Assumptions of r Linearity Bivariate normal distribution Slide

Bivariate Correlation Analysis
Slide Scatterplots Provide a means for visual inspection of data the direction of a relationship the shape of a relationship the magnitude of a relationship (with practice)

Interpretation of Coefficients
Slide Relationship does not imply causation Statistical significance does not imply a relationship is practically meaningful

Slide Suggests alternate explanations for correlation results X causes Y. . . or Y causes X or X & Y are activated by one or more other variables or X & Y influence each other reciprocally

Slide Artifact Correlations Goodness of fit F test Coefficient of determination Correlation matrix used to display coefficients for more than two variables

Bivariate Linear Regression
Slide 18 -7 Used to make simple and multiple predictions Regression coefficients Slope Intercept Error term Method of least squares

Interpreting Linear Regression
Slide Residuals what remains after the line is fit or (Yi-Yi) Prediction and confidence bands ^

Interpreting Linear Regression
Slide Goodness of fit Zero slope 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

Nonparametric Measures of Association
Slide Measures for nominal data When there is no relationship at all, coefficient is 0 When there is complete dependency, the coefficient displays unity or 1

Nonparametric Measures of Association
Slide Chi-square based measure Phi Cramer’s V Contingency coefficient of C Proportional reduction in error (PRE) Lambda Tau

Characteristics of Ordinal Data
Slide Concordant- subject who ranks higher on one variable also ranks higher on the other variable Discordant- subject who ranks higher on one variable ranks lower on the other variable

Measures for Ordinal Data
Slide No assumption of bivariate normal distribution Most based on concordant/discordant pairs Values range from +1.0 to -1.0

Measures for Ordinal Data
Slide Tests Gamma Somer’s d Spearman’s rho Kendall’s tau b Kendall’s tau c

Multivariate Analysis: An Overview
Chapter 19 Multivariate Analysis: An Overview

Selecting a Multivariate Technique
Slide Dependency dependent (criterion) variables and independent (predictor) variables are present Interdependency variables are interrelated without designating some dependent and others independent

Dependency Techniques
Slide Multiple regression Discriminant analysis Multivariate analysis of variance (MANOVA) Linear structural relationships (LISREL) Conjoint analysis

Uses for Multiple Regression
Slide 19- 3 Predict values for a criterion variable by developing a self-weighting estimating equation Control for confounding variables to better evaluate the contribution of other variables Test and explain causal theories Path analysis

Uses for Discriminant Analysis
Slide Classify persons or objects into various groups Analyze known groups to determine the relative influence of specific factors

Use for MANOVA Slide 19 -5 Assess relationship between two or more dependent variables and classificatory variables or factors samples Examples measure differences between employees customers manufactured items production parts

Uses of LISREL Slide Explains causality among constructs not directly measured Two parts Measurement model Structural Equation model

Two Models of LISREL Measurement Structural equation
Slide Measurement used to relate the observed, recorded, or measured variables to the latent variables (constructs) Structural equation shows the causal relationships among the latent variables

Use for Conjoint Analysis
Slide Market research Product development

Interdependency Techniques
Factor analysis Cluster analysis Multidimensional Scaling (MDS) Slide

Slide Factor Analysis Computational techniques that reduce variables to a manageable number construction of new set of variables based on relationships in the correlation matrix Principal components analysis Communalities Rotation Measurement statistics

Factor analysis Cluster analysis Slide

Steps in Cluster Analysis
Slide Select sample to be clustered Define measurement variables Compute similarities among the entities through correlation, Euclidean distances, and other techniques Select mutually exclusive clusters Compare and validate the clusters

Factor analysis Cluster analysis Multidimensional Scaling (MDS) Slide

Multidimensional Scaling
Slide Creates a special description of a respondent’s perception about a product, service, or other object of interest

Written and Oral Reports
Chapter 20 Presenting Results: Written and Oral Reports

Written Research Report
Slide Short report For well-defined, limited-scope problems with straight-forward methodology Usually 5 or fewer pages Formats Findings summary (graphical or tabular) attached to letter of transmittal Business letter Internal memorandum

Slide Short Report (Memorandum) Reason for writing Answer direct inquiry with specific answer and supporting detail Expository style with brevity and directness Attach detailed materials as appendices when needed

Slide Long report Technical report Management report

Long Report Components
Slide Prefatory Items Letter of transmittal Title page Authorization letter Executive summary Table of contents Introduction Problem statement Research objectives Background Methodology Sampling design Research design Data collection Data analysis Limitations Conclusions Summary and conclusions Recommendations Appendices Bibliography

Written Report Considerations
Slide Order of report Sentence outline Topic outline Comprehensibility Readability indices Pace Tone

Presentation of Statistics
Slide Text paragraph format Semi-tabular format Tabular format Graphical format

Graphical Formats Line graphs Area charts Pie charts Bar charts
Slide Line graphs Area charts Pie charts Bar charts Pictographs/Geo-Graphics 3-D graphics

Oral Presentations Preparation Content Delivery Length Content Style
Slide Preparation Length Content Style Scripted Extemporaneous Audiovisuals Type Role Content Opening Findings and conclusions Recommendations Delivery Vocal characteristics Physical characteristics

Audiovisual Aids Chalkboards Whiteboards Handout materials Flip charts
Slide Chalkboards Whiteboards Handout materials Flip charts Slides Overhead transparencies Computer-drawn visuals Computer animation

Part 1 Introduction to Business Research.

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Part 1 Introduction to Business Research.

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