Competitive Position® Salary Survey Reports
Salary Reports for Information Technology Professionals
Salary Results by Position, Skills, Experience and Location
Updated Quarterly - Complete Statistical Documentation
Membership Subscriptions and a Free Archive
by Whole Root® Economic Research, Inc.
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FAQ: View the complete list of Frequently Asked Questions.
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The Salary Survey Reports are an accurate appraisal of competitive salary offers in the job market. Each Salary Survey Report includes complete statistical documentation for result review and verification. The statistical tests results are held to a very stringent standard. The data sources are publicly available, everyone can examine the want ads. Statistically equivalent salary survey results could be reproduced by a qualified statistician following the identical methodology. The Competitive Position® Salary Survey Reports can be compared for accuracy against surveys that meet the same standards: a reviewable data source, verifiable statistical test results and the ability to be reproduced.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
Whole Root® Economic Research strongly holds that classified want ads collectively reflect the competitive demand and supply conditions of the computer job market. Want ads are an unbiased source of salary information.
Each want ad states an employer's initial bargaining position: potential salary versus desired qualifications. The goal of the listing is to elicit the best qualified candidate within the employer's cost constraints. This goal creates a competitive market for computer professionals that is displayed within the collection of classified want ads.
The success of a want ad depends on its competitive position relative to other want ads. If the salary is too low relative to the experience requirement, few suitable professionals will submit resumes. If the salary is too high relative to the experience requirement, the employer may overextend expenses for the desired job performance. The success of a want ad depends upon the cost-to-performance constraints of the employer relative to the salary offers and experience requirements listed in other want ads. The competition between employers for the best resumes restricts the distribution of salary offers relative to experience requirements around central tendency, or average values.
The income level of employers determines their cost constraints and performance needs and, in turn, the demand for computer professionals. When sales are good for employers the demand for computer professionals is strong and salary offers are high. When sales are bad for employers the demand for computer professionals is weak and salary offers are low. Importantly, the difference in income between employers accounts for some of the variation in salary offers.
The supply of job candidates determines the level of salary offers needed to entice the best qualified applicants. An excess supply of computer professionals in the job market is reflected in low salary offers. A short supply forces employers to make high salary offers. Employers adjust their salary offers and experience requirements to reflect the quality of resumes elicited by their want ads.
The competitive demand for and supply of computer professionals is reflected in the average, and distribution, of the salary offers and experience requirements of job listings. The average salary offer is determined by the performance needs, sales revenue and cost constraint of employers, in combination with the availability and alternative opportunities of computer professionals. The distribution of salary offers is determined by: the competitive rivalry between employers, the variation in profitability of employers, differences in the quality of skills employers desire, and the location of the job.
Career web sites and internet newsgroups are today's job market news. Each want ad is written in consideration of an employer's current needs and capabilities. Collectively, the classified want ads reflect up-to-date demand and supply conditions.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The Competitive Position® Salary Survey Reports present the results of a straight forward statistical analysis of want ads. The statistical methodology creates accurate and valid results. The want ad data is an authentic representation of the job market.
The Salary Survey Reports are based on want ads listed in publicly available sources such as career web sites and internet newsgroups. Surveyed want ads list a location, qualifications within the IT profession, a salary offer and an experience requirement.
The Job Titles are developed empirically, from the want ad data itself. A Job Title is formed when a set of qualifications is required in a significant number of want ads. The Job Titles are an indication of the positions and the associated hardware/software skills in demand. Due to differences in demand, some of the Job Titles have more specific qualifications than others.
The Salary Survey Reports are available for locations in the United States of America. Each Location corresponds to a metropolitan statistical area as defined by the U.S. Office of Management and Budget (OMB).
Each Salary Survey Report presents the combined results of 2 surveys. Job Title salary surveys are made for the United States of America. Location salary surveys are made for the information technology job markets. Together, the want ad data creates Salary Survey Reports about specific job markets for very detailed IT skills and positions.
The principal statistical technique of the salary survey is the Regression Analysis. This technique derives the 'best fit' equation between the salary offers and the job characteristics in the want ads surveyed. The 'best fit' is the average equation of the salary offer possessing the minimum variance between the want ads of the sample.
The regression equation expresses the mathematical relationship between the salary offer and the significant job characteristics. There is usually an entry level salary offer and a rate of increase based on years of experience. Wage inflation or deflation is a common component of the regression equation. Additional position and skill qualifications can also be components in the salary offer calculation.
The significance of each regression equation is confirmed by several statistical tests. The 95% collinearity test verifies that only the job characteristics that influence salary offers directly are applied in the regression equation. The significance of the regression equation and each of its components is verified using the F-Distribution and t-Distribution statistical tests. The regression equation is also tested and, if necessary, corrected for heteroscedasticity, a condition where the variance of the salary offers can be explained by known job characteristics. The F-Distribution and t-Distribution statistical tests and the heteroscedasticity correction (if applicable) are documented in each Salary Survey Report.
The salary information in each Salary Survey Report is calculated from a Job Title regression equation and a geographic adjustment ratio. This ratio is constructed from the Location regression equation associated with the Job Title and the regression equation of the Location of the Salary Survey Report. Details about the specific regression equations are fully documented in each Salary Survey Report.
Whole Root® Economic Research, Inc. has prepared the Competitive Position® Salary Survey Reports according to accepted statistical standards. Statistically equivalent salary survey results could be reproduced by a qualified statistician following the identical methodology.
Whole Root® Economic Research strongly holds that classified want ads collectively reflect the competitive demand and supply conditions of the computer job market. Want ads are an unbiased source of salary information.
Each want ad states an employer's initial bargaining position: potential salary versus desired qualifications. The goal of the listing is to elicit the best qualified candidate within the employer's cost constraints. This goal creates a competitive market for computer professionals that is displayed within the collection of classified want ads.
The success of a want ad depends on its competitive position relative to other want ads. If the salary is too low relative to the experience requirement, few suitable professionals will submit resumes. If the salary is too high relative to the experience requirement, the employer may overextend expenses for the desired job performance. The success of a want ad depends upon the cost-to-performance constraints of the employer relative to the salary offers and experience requirements listed in other want ads. The competition between employers for the best resumes restricts the distribution of salary offers relative to experience requirements around central tendency, or average values.
The income level of employers determines their cost constraints and performance needs and, in turn, the demand for computer professionals. When sales are good for employers the demand for computer professionals is strong and salary offers are high. When sales are bad for employers the demand for computer professionals is weak and salary offers are low. Importantly, the difference in income between employers accounts for some of the variation in salary offers.
The supply of job candidates determines the level of salary offers needed to entice the best qualified applicants. An excess supply of computer professionals in the job market is reflected in low salary offers. A short supply forces employers to make high salary offers. Employers adjust their salary offers and experience requirements to reflect the quality of resumes elicited by their want ads.
The competitive demand for and supply of computer professionals is reflected in the average, and distribution, of the salary offers and experience requirements of job listings. The average salary offer is determined by the performance needs, sales revenue and cost constraint of employers, in combination with the availability and alternative opportunities of computer professionals. The distribution of salary offers is determined by: the competitive rivalry between employers, the variation in profitability of employers, differences in the quality of skills employers desire, and the location of the job.
Career web sites and internet newsgroups are today's job market news. Each want ad is written in consideration of an employer's current needs and capabilities. Collectively, the classified want ads reflect up-to-date demand and supply conditions.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The complete Salary Survey Reports are statistically updated with newly posted want ads every quarter. The Selection Help Form, below, provides Completion Dates and other information about the want ad sources of each Salary Survey Report.
The Competitive Position® Salary Survey Reports are based on want ads listed in publicly available career web sites and internet newsgroups. Surveyed want ads list a location, qualifications within the IT profession, a salary offer and an experience requirement. Job Title salary surveys are made for the United States of America. Location salary surveys are made for the information technology job markets. Together, the want ad data creates Salary Survey Reports about specific job markets for very detailed IT positions and skills.
The want ad sources of the Job Title and Location salary surveys are fully documented. Each Salary Survey Report presents: the names of the career web site and internet newsgroup sources; the beginning and end dates of the research; and, the number of want ads statistically analyzed.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
To find the Salary Survey Report that's right for you please use this Selection Help Form to view: the Job Title and Location Salary Ranges, the detailed list of qualifications of each Job Title; the counties and towns included in each Location; the completion date; and, the specific table of contents of each Salary Survey Report.
The qualifications of the Job Title, the towns and counties of the Location, and the Completion Dates are presented as they appear in the Salary Survey Report. An explanatory table-of-contents outlines the complete Salary Survey Report available with a Membership Subscription.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The Salary Survey Reports are a valid appraisal of competitive salary offers in the job market. Each Salary Survey Report includes complete statistical documentation for result review and verification. The statistical tests results are held to a very stringent standard. The data sources are publicly available, everyone can examine the want ads. Statistically equivalent salary survey results could be reproduced by a qualified statistician following the identical methodology. The Competitive Position® Salary Survey Reports conform to very high standards: a reviewable data source, verifiable statistical test results and the ability to be reproduced.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
Complete documentation of the want ad data sources, the characteristic statistics and the statistical test results are presented and explained in each Salary Survey Report. An outline of the documentation follows below.
The Average Experience Requirement for the Job Title
The High and Low Range of Experience Requirements for the Job Title
Required Skills: the specific position and software/hardware skills, and their keyword variants, required for this Job Title
Other Desired Skills: the additional software/hardware skills, and their keyword variants, required in some want ads of this Job Title
Location Details: the cities, counties, municipalities, parishes and towns included in the Location
(Please Note: You do not have to be familiar with statistics to find this information useful. This documentation also provides statisticians with the required test information to substantiate the salary results.)
Information about the want ad sources of the Job Title and Location salary surveys, including: the names of the newspaper and internet newsgroup references, the beginning and end dates of the research, and the number of want ads obtained.
A. The Expected Salary Offers: explanation of the regression method and presentation of the regression equation
B. The Expected 95% Probability Range: explanation of the high to low ranges of the salary offers and presentation of the standard deviation, the confidence interval and the t-test of each and every variable in the regression equation
C. The Extreme Limits of a Salary Offer: explanation of the two-thirds and 95% high to low salary ranges and presentation of the standard deviation, R-squared, F-distribution and other statistics of the regression equation
A. The Geographic Adjustment ratio: explanation of the Location regression equations and presentation of the Geographic Adjustment calculation
B. Expected Salary Offers: explanation and presentation of the standard deviations, confidence intervals, t-tests, R-squared, F-distribution and other statistics of the Location regression equations
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The Competitive Position® Salary Survey has two parts. Job Title salary surveys are made for the United States of America. Location salary surveys are made for the information technology job markets. Together, the want ad data creates Salary Survey Reports about specific job markets for very detailed IT skills and positions.
The principal statistical technique of the salary survey is the Regression Analysis. This technique derives the 'best fit' equation between the salary offers and the job characteristics in the want ads surveyed. The 'best fit' is the average equation of the salary offer possessing the minimum variance between the want ads of the sample. The job characteristics include: the years of experience, inflation over time, the type of position and/or any extra qualifications.
The method of determining the 'best fit' equation of the salary survey begins by verifying that each of the job characteristics are unrelated to each other. The 95% collinearity test verifies that only the job characteristics that influence salary offers directly are applied in the regression equation. For example, in some want ads a 'senior programmer' might refer to a particular position and salary track in the hierarchy of a firm while in other want ads it might only be a code word for greater experience. The collinearity test determines whether a 'senior programmer' is a separate position or if the years of experience are always greater for want ads requiring it. If 'senior programmer' is related to years of experience, then it provides no more information about salary offers beyond what is already known from the years of experience.
The unrelated job characteristics are statistically tested to determine the 'best fit' salary offer equation. Not all of the job characteristics have an influence on salary offers. Some are such an integral part of the job that most want ads implicitly assume it but do not state it. Others describe the peculiarities of the working environment rather than an especially valued qualification. It may be that how employer's value a qualification has not reached a critical mass, or consensus, that allows a statistically significant salary offer to be determined. The important characteristics of years of experience and inflation over time are always tested both in their linear and log-linear forms to get the best measurement of the salary offer.
The regression equation expresses the mathematical relationship between the salary offer and the significant job characteristics. There is usually an entry level salary offer and a rate of increase based on years of experience. Wage inflation or deflation is not an uncommon component of the regression equation. Additional position and skill qualifications can also be components in the salary offer calculation.
The significance of each of the components of the regression equation is verified using the t-Distribution statistical test. This test determines the probability that a component contributes nothing to the salary offer. The lower the probability the more confidence is placed on the salary offer component. The t-Distribution statistical test results are set to a high quality level for each of the components in the salary offer equation. No component is accepted above a t-Distribution probability of 5%. Most components have a t-Distribution probability significantly less than 1%.
The significance of the entire regression equation is verified using the F-Distribution statistical test. This test determines the probability that the regression equation adds nothing to the calculation of the salary offer. The lower the probability the more confidence is placed in the regression equation. The F-Distribution statistical test result are set to a high quality level for the regression equation. There is usually less than a one-hundredth of a percent probability (<.01%) that there is no salary offer regression equation.
Many want ads state a salary offer that is either greater or less than what is expected by the regression equation. The difference between the salary offer found in a want ad and the expected salary offer is known as a residual. The variance, the total of the residuals for the entire sample of want ads, is tested against Heteroscedasticity.
Heteroscedasticity is a condition where a statistically significant relationship can be constructed between the variance of the salary offers and the job characteristics. It exists when at least one job characteristic influences the residuals. This occurs because employers are less in consensus on the value of some job characteristics and more in consensus on the value of other job characteristics. In the sample of want ads the difference between the high and the low salary offers may be larger: from one month to another, with higher experience requirements or with an extra qualification. If employers are less in agreement on the value of particular job characteristics, then this information needs to be incorporated into the salary offer regression equation.
A regression equation is derived between the variance in salary offers and the job characteristics. If this heteroscedasticity regression equation is statistically significant, the variance is calculated for each want ad and is applied in a new derivation of the salary offer regression equation. With this heteroscedasticity correction, the 'best fit' salary offer regression equation is found. If a regression equation can not be derived between the variance in salary offers and the job characteristics, then the original salary offer regression equation is the 'best fit'.
The salary information in each Salary Survey Report is calculated from a Job Title regression equation and a geographic adjustment ratio. This ratio is constructed from the Location regression equation associated with the Job Title and the regression equation of the Location of the Salary Survey Report. Details about the specific regression equations are fully documented in each Salary Survey Report.
The Expected Salary Offer is calculated by the regression equation for the Job Title and the geographic adjustment ratio at the Number of Years and/or Months of Experience of the Salary Survey Report. The Expected Salary Offer is: the most likely salary offer made in the marketplace; the average salary offer found in the want ads with the stated job requirements; and, the salary offer that is expected in the marketplace for a candidate well qualified in the requirements for this position.
The 95% Probability Range of the Expected Salary Offer is calculated from a pair of Job Title regression equation calculations and the geographic adjustment ratio. There is a 95% probability that the expected salary offer for the entire job market lies within this range.
To construct this 95% Probability Range each component of the Job Title regression equation is altered by a factor of its variation across want ads. This factor has two parts: the Standard Deviation, measuring the average variation above or below the regression equation component that can be expected to be found in a want ad; and, the point on the t-Distribution of the sample where only 2.5% of want ads have higher values. The product of the Standard Deviation and the t-Distribution probability point is added to, and subtracted from, the expected salary offer of each component to determine the high, and low, salary offer. The high, or low, salary offer for each component is added together in such a way to construct two adjusted regression equation calculations that minimize the expected salary offer 95% Probability Ranges. The geographic adjustment ratio is applied to both high and low calculations at the Number of Years and/or Months of Experience of the Salary Survey Report.
The Current Rate of Inflation per Year is calculated from the regression equation for the Job Title. The Wage Inflation factor is tabulated for One Year and is then divided by the Expected Salary Offer at the Average number of Years of Required Experience. The inflation factor is the average rate for this position.
The Raise in Salary Offer with One More Year of Experience is calculated by the regression equation for the Job Title and the geographic adjustment ratio at one more year than the Number of Years and/or Months of Experience of the Salary Survey Report.
The Extreme Limits of a Salary Offer indicate the high and low salary offers that can be found in the want ads of the Salary Survey Report. The Two-Thirds and 95% ranges mark the probability distribution of want ads. Only One-Third of want ads state a salary offer greater or less than the Two-Thirds High and Low Salary Offers. This range contains salary offers found in 68% of the want ads. Only 5% of want ads state a salary offer greater or less than the 95% Top and Bottom Salary Offers. This range contains salary offers found in 95% of the want ads.
The Extreme Limits of a Salary Offer are calculated by adding, and subtracting, a factor of the variance to, and from, the Expected Salary Offer. This factor has two parts: the Standard Deviation, measuring the average residual found in a want ad; and, the point on the t-Distribution of the sample with the desired probability. For the Two-Thirds range the point on the t-Distribution where only 16% of want ads have higher values is chosen. For the 95% range the point on the t-Distribution where only 2.5% of want ads have higher values is chosen. The geographic adjustment ratio is applied to both the Two-Thirds and 95% ranges at the Number of Years and/or Months of Experience of the Salary Survey Report.
Whole Root® Economic Research, Inc. has prepared the Competitive Position® Salary Survey Reports according to accepted statistical standards. Statistically equivalent salary survey results could be reproduced by a qualified statistician following the identical methodology.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The principal statistical technique of the Competitive Position® Salary Survey Reports is the regression analysis. This technique is superior to the analysis found in most publicly available salary surveys. The regression analysis is preferred because it analyzes all of the data together and it statistically tests the results.
The purpose of a salary survey is to determine a salary for a set of job characteristics such as a Job Title, Location and Number of Years and/or Months of Experience. The average and high-low range of salaries for a particular set of job characteristics is usually desired.
If all IT salaries and the activity in the entire job market were known it would be easy to determine the salary for a set of job characteristics. However it is not possible to know the salaries of every information technology professional nor the hiring plans of every employer, only a sample can be studied. The estimate of the salaries from a sample must be confirmed to be representative of the entire job market to a high degree of probability.
The regression analysis offers several probability tests for the quality of its estimated salaries. The collinearity test verifies that only the job characteristics that influence salary offers directly are included in a salary calculation. The accuracy of a salary estimate is verified using the F-Distribution and t-Distribution probability tests. The regression equation is also tested and, if necessary, corrected for heteroscedasticity, a condition where the variance of the salary offers can be explained by known job characteristics. The F-Distribution and t-Distribution statistical tests and the heteroscedasticity correction (if applicable) are documented in each Salary Survey Report.
In contrast to the Competitive Position® Salary Survey Reports, most publicly available salary surveys do not offer probability tests results for their salary estimates. Typically a simple mean salary is estimated from a sample of IT professionals with the same years of experience. Several of these salary estimates for different years of experience are presented implying a relationship between salary and experience. However, no statistical test is applied to find the probability that the samples actually depict a relationship between salary and experience. Moreover, each salary estimate is based on its own small sample. It is likely that the sample will include an IT professional with an extremely high or low salary that skews the estimate away from its true value. By accounting for the level of variation, a salary estimate based on the complete sample has a higher probability of accuracy.
The regression analysis applied in the Competitive Position® Salary Survey Reports derives the 'best fit' equation between the salary offers and the job characteristics in the want ads surveyed. The 'best fit' is the average equation of the salary offer possessing the minimum variance between the want ads of the sample. The salary information presented in the Salary Surveys Reports are of the highest statistical quality.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The Competitive Position® Salary Survey Reports are based on want ads listed in publicly available career web sites and internet newsgroups. The want ad sources are fully documented, each Salary Survey Report presents: the names of the career web site and internet newsgroup sources; the beginning and end dates of the research; and, the number of want ads statistically analyzed.
Surveyed want ads list a location, qualifications within the IT profession, a salary offer and an experience requirement. In want ads listing more than one salary offer or experience requirement the following rules apply. If a want ad provides a range of 2 salary numbers with only one experience requirement then only the lowest salary number is recorded. For a want ad listing a range of 2 experience numbers with only one salary offer, only the highest experience number is recorded. Want ads that provide both a range of Salary numbers and a range of Experience numbers are recorded as two separate entries. The Low Salary number is recorded with the Low Experience number. The High Salary number is recorded with the High Experience number.
The Job Titles are developed empirically, from the want ad data itself. A Job Title is formed when a set of qualifications is required in a significant number of want ads.
A Job Title of a Salary Survey Report refers to a set of information technology qualifications. A position -such as administrator, developer, engineer, programmer or support- is a typical qualification. One or more skills in the use of computer hardware and/or software -such as programming languages, databases, applications, systems, networks, communications and the internet- are usually linked with a position to form a Job Title. For instance the title "C++ and Java Programmer on the UNIX Platform" specifies two programming languages, a position and the computer hardware.
The Job Titles are an indication of the positions and the associated hardware/software skills in demand. Due to differences in demand, some of the Job Titles have more specific qualifications than others.
Job Title salary surveys are made for the United States of America. Location salary surveys are made for the information technology job markets. Together, the want ad data creates Salary Survey Reports about specific job markets for very detailed IT skills and positions. Want ads are continuously added to the survey to maintain up-to-date Salary Survey Reports.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
One advantage of using career web site and internet newsgroup sources for want ads is that the data is publicly available. Open your browser, find a career web site and read the want ads that form the basis for the Salary Survey Reports. You can also open your internet newsreader, subscribe to a newsgroup and read the want ads. The Salary Survey Reports allow the user to become familiar with the source of data and know specifically what is being analyzed.
Whole Root® Economic Research does not distribute or reproduce want ads. The Salary Survey Reports do not identify individual want ads.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
The raw data of the Salary Survey Reports are want ads anonymously obtained from publicly available career web sites and internet newsgroups. Whole Root® Economic Research has never requested or obtained customized, altered or proprietary want ads designed explicitly for a salary survey from any individual or any public or private organization. By directly observing market positions in the "wild", interview and non-random volunteer biases are avoided.
Surveyed want ads list a location, qualifications within the IT profession, a salary offer and an experience requirement. Statistically equivalent salary survey results could be reproduced by a qualified statistician following the identical methodology.
FAQ: Return to the place of this question on the list of Frequently Asked Questions.
Accuracy: View the "Accuracy, Dates and Validity" section of Frequently Asked Questions, above.
Whole Root® Economic Research, Inc. is an independent research company. The Competitive Position® Salary Survey Reports are produced in their entirety without the assistance or endorsement of any other public or private organization. All revenue is earned from the sale of the Salary Survey Reports. No financing or revenue is received from any government or private organization outside of the direct sale of the Salary Survey Reports. The need to produce for public sale removes "hidden agenda" biases and creates a focus on accuracy and validity.
Whole Root® Economic Research, Inc. has prepared the Competitive Position® Salary Survey Reports according to accepted statistical standards. Statistically equivalent salary survey results could be reproduced by a qualified statistician following the identical methodology.
The raw data of the Salary Survey Reports are want ads anonymously obtained from publicly available web sites and internet newsgroups. Whole Root® Economic Research has never requested or obtained customized, altered or proprietary want ads designed explicitly for a salary survey from any individual or any public or private organization. Whole Root® Economic Research does not print, post or provide access to any individual want ad in whole or in part.
The statistics present average and variance information about the sample of want ads. Possible biases and other errors may exist within the sources of the sample that Whole Root® Economic Research, Inc. is not responsible for. Individual want ads and job placements can not be identified. Job placement and/or salary improvement is not guaranteed nor offered.
All web sites and internet newsgroups that post, list or make available publicly accessible want ads are not associated with, do not endorse and are not responsible for the Competitive Position® Salary Survey Reports or Whole Root® Economic Research, Inc. in anyway.
All corporations, organizations and institutions providing want ads for public access are not associated with, do not endorse and are not responsible for the Competitive Position® Salary Survey Reports or Whole Root® Economic Research, Inc. in anyway.
All corporations, organizations and institutions involved in the design, development, production, distribution and/or application of information technology hardware, software and/or services are not associated with, do not endorse and are not responsible for the Competitive Position® Salary Survey Reports or Whole Root® Economic Research, Inc. in anyway.
The raw data of the 1995 through 1998 editions of the Salary Survey Reports included want ads anonymously obtained from publicly available newspapers. The New York Times, the Washington Post and all other newspaper publishers are not associated with, do not endorse and are not responsible for the Competitive Position® Salary Survey Reports or Whole Root® Economic Research, Inc. in anyway.
The inspiration behind the Competitive Position® Salary Survey Reports is "excellence at a bargain". Everyone can now have easy access to sophisticated market analysis
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