TDM 402 Test 4

• 1. Identify the Model Objectives
• 2. Formulate the Hypothesized Model Structure
• 3. Operationalize the Variables

• 1.Testable Hypothesis
• 2.Forecasts
• 3.Simulations

• *Proposed Relationships
• *Preliminary Framework
• *Classification system

• 1. Conceptualization
• 2. Nominal Definition
• 3. Operational Definition
• 4. Measurements in the Real World

* non-constant characteristics or conditions that change or have different values for different individuals or observations (r).

*They are the focus of quantitative research projects which is interested in their levels (means), spreads (variances) and relationships (covariances)

* the process of assigning numbers to variables for observational units.

Percieved relationship is due to simple, positive directional causes.

• EX: An increase in income causes increase in vacation travel
• 

* Percieved relationship is due to common uncerlying casual factor

• EX: An increasex in Income causes increases in both Travel and Grocery Expenditures which appear to be realted.
• 

* Perceived simple relationship is confuounded by other causes

• EX: Changes in Travel are Caused both by changes in Income and confounded by changes in Tourism Advertising.
• 

* Percieved relationship is due to random correlations

EX: Changes in Travel and Cancer Deaths over tiem are not casually realted

causal

common response

• confounded
• a bunch of other things that are going on

• common cause
• same things that are driving one up are driving the other one up

• 1. Conceptualization: Ideas « Concepts
• 2. Nominal Definition
• 3. Operational Definition
• a. Observables (Direct and Indirect)
• b. Constructs and Indicators
• 4. Measurements in the Real World
• a. Ranges and variation
• b. Dimensions
• c. Levels (nominal, ordinal, interval and ratio)

• o Dimensions
• - the attributes and ranges of meanings that are relevant to the concept.
• o Levels of measurement
• - nominal, ordinal, interval and ratio.
• o Range of variation
• · variation is crucial to statistics for measuring the degree of certainty (reliability)
• ·covariation provides information for measuring relationships between variables.

·

• 1. Nominal
• 2. Ordinal
• 3. Interval
• 4. Ratio

- Variables whose attributes merely label characteristics (names)

EX: name, gender, political party, birthplace, group type (friends, family, etc.).

variables with attributes we can logically order in relative terms (ranks)

EX: rankings, preference choices, motivation scales, attitude measures, satisfaction or importance rankings. (Months)

The logical distance between attributes can be expressed in meaningful standard intervals (equal distance between levels but no true zero point).

EX: month of year, time of day, temperature in Fahrenheit or Celsius, consumer price index.

attributes have all the structural characteristics of interval variables, but have a “true‘ zero reference point. (equal distance between levels with true zero point)

• EX: income, education, frequency of participation, visitor-days, trip expenditures,
• counts of checkmarks.

• a representation (usually mathematical) of some behavior including the variables and the assumed
• causal relationships

• information gathered through the human senses.
• In statistics, one piece of sample data

• Characteristics or conditions that change or have different values for different individuals or
• observations.

the mental process whereby fuzzy and imprecise concepts are made more specific and precise

limiting the specifications assigned to a term. Assigning a name to a concept

the development of specific research procedures that will result in empirical observations. (dimensions, range of variation, levels of measurement)

is the process of assigning numbers to variables for observational units

the spread of or dispersion of observed values within a set of data

the degree to which two variables change together (in the same or opposite directions)

a hypothesis that is capable of generating predictions (not necessarily forecasts) for evaluating its likelihood

is a probabilistic statement that something will happen based on what is already known. Usually, but not always for the future

a "best" prediction of the future made by a particular person or with a particular technique or representation of current conditions

a general direction in which something tends to move over time.

• Demand = f(travelers, destination,
• relationship)
• Travelers
• Destination
• Relationship

Travelers

Destination

Relationships

• One type of ‘survey instrument
• A printed/written list of questions

Whole process of conducting an investigation, which involves a number of ‘subjects’

• person who records answers to a survey questionnaire and assists the respondent with
• interpretation.
• ·
• Questionnaires are ideal for obtaining policy-related data.
• They use a transparent methodology.
• Quantification is easily communicated/ understood.
• Repeat surveys can study changes over time.
• They can cover a wide range of activities, attitudes, meanings, and perceptions.

• the entire collection of items or persons that is the focus of concern.
• (e.g. the population of potential tourists)

• a set of items or number of subjects
• that have been selected from a population.
• (e.g. a sample of 20 tourists.)

person who is selected and interviewed for a survey

the number of respondents who complete a questionnaire compared to the number who were asked.

• person who records answers to a survey questionnaire and assists the respondent with
• interpretation.

• 1. Interviewer-completion
• 2. Respondent-completion
• 3. Combinations of Respondent and Interviewer – completion

interviewer conducts interview based on questionnaire, and records answers on the questionnaire

respondents fill out the questionnaire themselves

: e.g. interviewer records observable characteristics (group size, gender, travel mode) and the respondent is asked to write down confidential information (income, expenditures).

• 1. The interest of the respondent in the survey topic
• 2. The length of the questionnaire
• 3. Questionnaire design/presentation/complexity
• 4. The style, content and authorship of the accompanying letter and introduction
• 5. The provision of a postage-paid reply envelope or easy submission if electronic
• 6. Rewards/ incentives for responding
• 7. The number and timing of reminders/follow-ups.

• a. Open-ended or direct questions
• b. Checklist
• c. Ranking Likert
• d. Scales
• e. Semantic differential.

sample

representative

Random sampling

• mean
• variance
• covariance

• the desired precision
• research budget
• size of the population

Confidence Intervals

level of precision

weighting