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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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Sample - Refers to a subset of elements selected from a population. A sample should be randomly selected and representative of the population.

Sampling Frame - The list of population elements from which the sample will be drawn.

Sample Survey - Cross-sectional study in which the sample is selected to be representative of the target population and in which the emphasis is on the generation of summary statistics such as averages and percentages. Also called a field survey.

Sampling Control - Term applied to studies relying on questionnaires and concerning the researcher's dual abilities to direct the inquiry to a designated respondent and to secure the desired cooperation from that respondent.

Sampling Distribution - Distribution of values of some statistic calculated for each possible distinguishable sample that could be drawn from a parent population under a specific sampling plan.

Sampling Error - Difference between the observed values of a variable and the long-run average of the observed values in repetitions of the measurement.

Sampling Units - Nonoverlapping collections of elements from the population.

Secondary Data - Statistics not gathered for the immediate study at hand but for some other purpose.

Secondary Source - Source of secondary data that did not originate the data but secured them from another source.

Select-a-Response Question - Questions offering a set of options for a respondent to chose from as a response.

Selection Bias - Contaminating influence in an experiment occurring when there is no way of certifying that groups of test units were equivalent at some previous time.

Self-Report - Method of assessing attitudes in which individuals are asked directly for their beliefs about or feelings toward an object or class of objects.

Sentence Completion - Questionnaire containing a number of sentences that subjects are directed to complete with the first words that come to mind.

Sequence Bias - Distortion in the answers to some questions on a questionnaire because the replies are not independently arrived at but are conditioned by responses to other questions.

Sequential Sample - Sample formed on the basis of a series of successive decisions. If the evidence is not conclusive after a small sample is taken, more observations are taken; if still inconclusive after these additional observations, still more observations are taken. At each stage, a decision is made about whether more information should be collected or whether the evidence is sufficient to draw a conclusion.

Simple Linear Regression - The statistical technique for finding the best fitting straight line for a set of data. This technique is called regression and the resulting line is called the regression line or least squares line.
Simple Random Sample - Probability sample in which each population element has a known and equal chance of being included in the sample and in which every combination of n population elements is a sample possibility and is just as likely to occur as any other combination of n units.

Simple Regression and Correlation - Procedures that examine the relationship between two interval-ratio variables for the same elements.

Simple Tabulation - Count of the number of cases that fall into each category when the categories are based on one variable.

Skip Pattern - The logical organization of an interview or questionnaire so that questions are asked only of those who fit certain criteria. Other respondents are directed elsewhere in the questionnaire depending on the criteria they meet.

Snowball Sample - Judgment sample that relies on the researcher's ability to locate an initial set of respondents with the desired characteristics; these individuals are then used as informants to identify still others with the desired characteristics.

Spearman's Rank Correlation Coefficient - Nonparametric measure of dependence between two variables based on the correlation between the ranks of the observations.

Spurious Correlation - Condition that arises when there is no relationship between two variables but the analyst concludes that a relationship exists.

Spurious Noncorrelation - Condition that arises when the analyst concludes that there is no relationship between two variables but, in fact, there is.

Stability - A technique for assessing the reliability of a measure by measuring the same objects or individuals at two different points in time and then correlating the scores; the procedure is known as test-retest reliability assessment.

Standard Deviation - The positive square root of the average squared distance of the population or sample values from the mean. It is the most widely accepted measure of dispersion.

Standard Error - Standard deviation of the distribution of sample means. It is the standard distance between the sample means and the population means by chance (how much error to expect by chance).

Standard Error of Estimate - Term used in regression analysis to refer to the absolute amount of variation in the criterion variable that is left unexplained or unaccounted for by the fitted regression equation.

Standard Normal Distribution - The distribution of z-scores, which always has a mean of 0 and a standard deviation of 1.

Standardized Scores (z-scores) - To standardize a distribution, scores (x values) are transformed into z-scores by using the mean and standard deviation. A z score specifies the precise location of each x value within a distribution. The z-scores will form a standardized distribution that can be directly compared to other distributions that also have been transformed into z-scores. A z score has two components: sign and magnitude. The sign of the z-score (+ or -) signifies whether the score is above the mean (+) or below the mean (-). The numerical value of the z-score specifies the distance from the mean by counting the number of standard deviations between the score and the mean.

Statistics - Calculations made when dealing with a sample. Statistics can be used to describe the sample, make inferences to the population (estimate parameters), or test hypotheses.

Stereotyping - The tendency to assign an individual to a group or broad category and then attribute generalizations about the group to the individual.

Stratified Sample - Probability sample that is distinguished by the two-step procedure in which (1) the parent population is divided into mutually exclusive and exhaustive subsets, and (2) a simple random sample of elements is chosen independently from each group or subset.

Structure - Degree of standardization imposed on the data collection instrument.

Symmetrical Distribution - When the values in a distribution are graphed, the right hand side of a symmetrical distribution is a mirror image of the left hand side. In a symmetrical distribution with one mode, all three measures of central tendency are all on one value.

Systematic Error - Error in measurement that is also known as constant error, since it affects the measurement in a systematic way.

Systematic Sample - Probability sample in which every kth element in the population is designated for inclusion in the sample after a random start.