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Methodist Healthcare

"We have been partnering with Superior DataWorks since 2005 and we have always trusted their team to meet our marketing research needs. Whether we require assistance with an online, phone or mailed survey, they are always prompt, professional, accurate and proactive. We really appreciate their flexibility with our ever-changing needs and helping us meet our strategic goals and objectives."
~ Cori Grant, MS, MBA

Homewood Suites by Hilton
"We have seen dramatic increases in both customer and employee satisfaction since utilizing Superior DataWorks."
~ Frank Saitta
Choice Hotels International
"I've always had great success when I've worked with Superior DataWorks. Each project is always done thoughtfully, efficiently and professionally. On my last mystery shopper project, they really added value to the research by including insights that another vendor might not have noticed."
~ David Ginsburg
International Paper
"Superior DataWorks was fast, efficient, economical, and creative in their work for International Paper. In helping us improve customer service, they gave outstanding customer service and support. I highly recommend Superior DataWorks."
~ Rick Carpenter
Hilton Hotels
"We have used Superior DataWorks for over five years conducting surveys, shopping calls, and data collection. The team has been creative in developing unique solutions to our data needs as well as rapidly completing the projects on-time, and on budget."
~ Bill Petschonek
Choice Hotels International
"Thank you for all of your efforts to successfully complete the second annual U.S. Franchisee Survey. In completing comprehensive interviews with over 1,000 of our hotel owners and general managers, you have provided our Board of Directors and senior management invaluable insights for strategic planning. Thank you for the many hours and much thinking devoted to ensuring the accuracy of the results."
~ Catherine Shaw


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Causal Research - Research design in which the major emphasis is on determining a cause-and-effect relationship.

Central-Limit Theorem - Theorem that holds that if simple random samples of size n are drawn from a parent population with mean m and variance s^2, then when n is large, the sample mean will be approximately normally distributed with the mean equal to m and variance equal to (s^2)/n. The approximation will become more and more accurate as n becomes larger.

Chi-square Goodness-of-Fit Test - Used to test if a sample of data came from a population with a specific distribution.

Chi-square Test - Nonparametric procedure used to test if the standard deviation of a population is equal to a specified value. There are two types of chi-square tests: test for goodness of fit and test for independence.

Chi-square Test for Independence - Used to test the relationship between two different categorical factors for contingency.

Class Interval - By grouping the values of a distribution into classes, the data is easier to read and to analyze. The class interval is the width of each grouping of data.

Closed-Ended Questions - Questions characterized by the condition that responses are limited to a set of given options or ranges, such as rating scales. Also called fixed-alternative questions.

Cluster Sample - A probability sample distinguished by a two-step procedure in which (1) the parent population is divided into mutually exclusive and exhaustive subsets, and (2) a random sample of subsets is selected.

Coding - Technical procedure by which data are categorized; it involves specifying the alternative categories or classes into which the responses are to be placed and assigning code numbers to the classes.

Coefficient of Determination - The square of the coefficient of correlation. Measures goodness-of-fit (how well or tightly the data fit the estimated model). Takes on values between 0 and 1, with values closer to 1 implying a better fit.

Cohort - The aggregate of individuals who experience the same event within the same time interval.
Comparative Rating Scale - Scale requiring subjects to make their ratings as a series of relative judgments or comparisons rather than as independent assessments.

Completely Randomized Design - Experiment design in which independent random samples are drawn from each of the populations of interest.

Computer-Assisted Interviewing - The conducting of surveys using computers to manage the sequence of questions in which the answers are recorded electronically through the use of a keyboard.

Confidence Interval - The range around a survey result for which there is a high statistical probability that it contains the true population parameter.

Confidence Level - The probability that a particular confidence interval will include the true population value.

Conjoint Analysis - A method for establishing respondents’ utilities or evaluations based on the preferences they express for combinations of product attributes and features. Price is typically one of the attributes included.

Constant Sum Method - A type of comparative rating scale in which an individual is instructed to divide some given sum among two or more attributes on the basis of their importance to him or her.

Content Validity - Approach to validating a measure by determining the adequacy with which the domain of the characteristic is captured by the measure: it is sometimes called face validity.

Contingency Table - Two-dimensional table used to display the data of a chi-square test for independence.

Continuous Variables - Variables that can theoretically have an infinite number of values between adjacent units on the scale. Successive refinements of the measuring instrument yield increasingly precise values of a continuous variable. Examples are time, weight, and height.

Convenience Sample - Nonprobability sample sometimes called an accidental sample because those included in the sample enter by accident, in that they just happen to be where the study is being conducted when it is being conducted.

Correlation - The statistical technique used to measure and describe a relationship between two variables. It measures three characteristics of the relationship between two variables: direction (positive or negative), form (straight line or curved line), and degree (how strong or weak the relationship is).

Cross-Sectional Study - Investigation involving a sample of elements selected from the population of interest at a single point in time.
Cross Tabulation - A method of analyzing data that lets the analyst look at the responses to one question in relation to the responses to one or more other questions.