Statistical programming involves doing computations to aid statistical analysis. Statistical programming includes using statistical programming languages for summarizing & displaying data; fitting a model to data and finally displaying results.
We provide high quality professional statistical programming solutions for your particular needs. Programs can be written for personal use and tailored to your data, or written for possible publications in journals.
We offer a wealth of statistical programming excellence and experience. In addition to academia, we deliver expert statistical analyses and programming across a range of industry sectors including Pharmaceutical, Insurance, Finance, Sensory, Consumer Analysis, Sports and Energy.
Our statisticians and programmers have built a reputation of excellence by being responsive and collaborative, producing quality deliverables, and maintaining the highest level of scientific integrity.
Our consultants have substantial statistical knowledge and experience. Coming from a wide variety of academic and commercial backgrounds our statisticians frequently participate in rigorous training sessions to reinforce fundamental practices and explore cutting-edge methodologies.
Our statistical programmers and Data Management team can help you in all the ways of generating and maintaining codes for any kind of statistical analyses with SAS, R, S-Plus, Stata, Matlab, Python, Java, SQL, and other integrated languages.
Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data. According to Shamoo and Resnik (2003) various analytic procedures “provide a way of drawing inductive inferences from data and distinguishing the signal (the phenomenon of interest) from the noise (statistical fluctuations) present in the data”.
An essential component of ensuring data integrity is the accurate and appropriate analysis of research findings. Improper statistical analyses distort scientific findings, mislead casual readers (Shepard, 2002), and may negatively influence the public perception of research.
There are a number of issues that researchers should be cognizant of with respect to data analysis. These include:
Having the necessary skills to analyze
Selecting the best appropriate analysis technique
Providing honest and accurate analysis
Drawing unbiased inference
Following acceptable norms for disciplines
Manner of presenting data
Our highly skilled statisticians are always ready to provide you the best service with your data. Our statisticians are all highly qualified with solid background in both theoretical and applied statistics as well as experienced of working in numerous data analysis projects in diverse disciplines including social sciences, economics, engineering, medical sciences, public health, psychology, business, education, nursing etc. We are equally experienced in working on data analysis projects for clients from both academia and industry.
We guarantee to offer you analyses of your data sound in every aspect of quality. Our reputation and testimonies earned from clients of numerous projects we have completed in past give us confidence to request you to consider our service for your data analysis purpose.
Our comfort with virtually all higher-level quantitative methodologies and our expertise in applying these tools enables us to assist with virtually any of your data problem. Here is a sample of some of the analytical tools with which we are familiar:
• Various forms of Regression Analysis, including Non-Linear Regression and Ridge Regression
• Survival Analysis including Life Tables, Kaplan-Meier Analysis and Proportional Hazard Regression
• Time Series Analysis, including Vector Autoregression (VAR), Vector Error-correction Models (VECM), and GARCH and its variants (NGARCH, EGARCH, etc.)
• Panel Analysis
• Survey Development and Reliability/Validity testing of existing surveys
• Statistical Power Analysis for Sample Size determination
• Multivariate Analysis (with multiple outcome variables), such as MANOVA and MANCOVA.
• Qualitative analytical methods including Phenomenological Analysis and Grounded Theory
• Optimization methods such as Linear and Nonlinear Programming, Genetic Search, and Simulated Annealing
• Markov Chain Monte Carlo and similar methods
• Nonparametric Methods
• Zero-Inflated Count Models
• TURF, Thurstone Scaling, and Shapley Values (used often in marketing-related projects)
• Conjoint Analysis, Choice Modeling, and Maximum Difference Scaling (MaxDiff)
• Meta-Analysis
• Structural Equation Modeling (SEM), Confirmatory and Exploratory Factor Analysis (CFA and EFA), Multidimensional Scaling, and Path Analysis
• Neural Nets
• Data Mining, Machine Learning and Artificial Intelligence (AI)
• Parallel Computing to handle very large datasets and for problems that would otherwise take excessive computing time
• Various Bootstrapping and Jackknife techniques
• Spatial Analysis
• All statistical software packages including R, Matlab, SAS, Stata, MPLUS, LISREL, EQS, PASS, Maple, Mathematica, and SPLUS
For clients working with us on their data analysis, the procedure usually goes as follows:
We first review your methodology, survey instrument, and dataset in order to better understand your study and develop a plan of attack for the analysis and interpretation.
Next, we discuss your study with you via phone and/or email (whichever you prefer) to be sure that we are clear on what you wish to accomplish.
Depending on the state of your current dataset, and your software of choice for the analysis, we may or may not need to assist with data import and formatting. This is done completely free of charge, and typically takes less than a day.
Once all the preliminaries are taken care of, and we have a better idea of what exactly you need in the results, we will conduct the statistical analysis of the data. Unlike many other consulting service providers, we are proficient with virtually every statistical method and test, and various statistical software packages including SPSS, SAS, STATA, R, SPlus, MATLAB, EViews, MPlus, LISREL/AMOS/EQS for structural equation modeling, and many others.
We will then work with you to draft your results. This will include the outputs of our analysis (figures, tables, etc.), all in APA format (or any other format you require), along with a detailed summary of the findings. From the time we have the final/cleaned data set; we ordinarily can return a first draft of your results within 3-5 days.
From here, our job is not done. We will now work with you extensively to address any revisions you’d like, explain to you how to interpret the results, provide ample instruction on the methods used (and why) and what the results mean, suggest reading materials for you to greater understand the particular statistical methods used, and allow unlimited e-mail and phone support to ensure that you completely understand the results of the analysis and can discuss them freely. This also includes all revision requests from your committee. We take pride in our ability to coach you and hold your hand during this process, and will remain with you until the very end.
References
Shamoo, A.E., Resnik, B.R. (2003). Responsible Conduct of Research. Oxford University Press.
Shepard, R.J. (2002). Ethics in exercise science research. Sports Med, 32 (3): 169-183.
Structural Equation Modeling (SEM) is a multivariate statistical analysis technique that is used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis, and it is used to analyze the structural relationship between measured variables and latent constructs. This method is preferred by the researcher because it estimates the multiple and interrelated dependence in a single analysis. In this analysis, two types of variables are used endogenous variables and exogenous variables. Endogenous variables are equivalent to dependent variables and are equal to the independent variable.
The basic steps SEM works in are:
Defining individual constructs
Developing the overall measurement model
Design the study to produce the empirical results
Assessing the measurement model validity
Specifying the structural model
Examine the structural model validity
We have extensive experience in the area of SEM Analysis. In the past, we had the opportunity to build Structural Equation Models for a variety of applications, including loyalty tracking studies, market structure models, customer satisfaction, psychology, education and many more.
Structural Equation Modelling is a powerful multivariate analysis technique that includes specialized version of a number of other analysis methods as special cases. Being a sophisticated theoretical tool, Structural Equation Modelling is definitely not easy to implement.
Our expert Statistical Consultants are offering you the best services during all stages of your Structural Equation Modelling project requirements.
Our consultants have expertise with virtually every statistical software package for Structural Equation Modelling including MPLUS, LISREL, AMOS, EQS, R Stata and SAS.
How to discover value in mountain of data? Data mining uses sophisticated statistical analysis and modelling techniques to uncover patterns and relationships hidden in organizational databases. Data mining and knowledge discovery aim at tools and techniques to process structured information from databases to data warehouses to data mining, and to knowledge discovery.
The continuing rapid growth of on-line data and the widespread use of databases necessitate the development of techniques for extracting useful knowledge and for facilitating database access. The challenge of extracting knowledge from data is of common interest to several fields, including statistics, databases, pattern recognition, machine learning, data visualization, optimization, and high-performance computing.
The data mining process involves identifying an appropriate data set to “mine” or sift through to discover data content relationships. Data mining tools include techniques like case-based reasoning, cluster analysis, data visualization, fuzzy query and analysis, and neural networks. Data mining sometimes resembles the traditional scientific method of identifying a hypothesis and then testing it using an appropriate data set. Sometimes however data mining is reminiscent of what happens when data has been collected and no significant results were found and hence an ad hoc, exploratory analysis is conducted to find a significant relationship.
Extracting information from a data set and then transforming it into an understandable structure which can be used further is the goal of data mining process. The other process involved are interestingness metrics, data pre-processing, data management aspects, post-processing of discovered structures, complexity considerations, model and inference considerations, visualization, and online updating. Now days it is used by companies which have strong consumer focus – financial, retail, communication, and marketing organizations.
Our data mining consulting will help put you on the fast track to accurate and impressive results by utilizing the information you already have. We can help you predict specific outcomes based on your current data and formulate strategies for even greater improvement. Our data mining for business intelligence recognizes your unique environment and is formulated to best suit your needs in order to provide optimum results. We want to provide immediate and actionable insight so you can formulate a well-structured solution to get your business moving in the right direction.
Our data mining services will assist you in expanding your customer base by analyzing existing data, and accurately assessing risk management. We have the software and the expertise to help you make more effective business decisions by identifying new opportunities, to give you a significant edge over your competitors.
Our data mining consulting offers you the following supports:
Determine the feasibility of completing a successful data mining project.
o By defining data mining, aligning business objectives, and determining all data sources needed to mine through a single data table.
Prepare data for building data mining models.
o By identifying and correcting data problems, identifying and creating new features, and extracting samples from the database(s).
Develop a data mining model solution to business objectives.
o By identifying data mining methods to use and creating actionable models for execution.
Deploy data mining models by creating software infrastructure that uses data mining models to score new data.
o By developing software to complete the deployment plan, and test the software to ensure accurate deployment of the models.
We offer to provide data mining solutions using any software of your choice. In past, most of our clients wanted us to use software environments such as R, Matlab, Weka, Rapid/Miner, KMINE, SAS Enterprise Miner, IBM SPSS Modeler etc.
Machine learning is one of the forms of artificial intelligence that enables the computers to learn without being explicitly programmed. It focuses on the development of those programs which can enable smooth functioning even when exposed to new data. To sum up, machine learning is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behavioral strategies based on empirical data.
Data mining and machine learning are almost similar; to look for patterns both of them search data. What differs in both cases is that in machine learning the data is used to improve the program’s own understanding. Machine learning encompasses all data mining methods that can be implemented as an automated process.
Our machine learning experts are always ready to help you with any of your machine learning problems. We have vast experience of proving supports to a large set of clients with numerous machine learning techniques including but not limited to:
• Decision Trees, Random Forests
• Support Vector Machines (SVM) for regression and classification
• Cluster Analysis
• Artificial Neural Network Models (ANN)
• Bayesian Statistics: Naive Bayesian Classifier, Bayesian Hypothesis Testing
• K – Nearest Neighbors (KNN) for Regression and Classification
• Ensemble Models and “voting” Approaches to Modeling
• Adaboost and other boosting techniques
• Bootstrapping
• Genetic Algorithms
• Non-Parametric Regression
• Time Series Analysis by Fourier Transform
• Monte Carlo Method
• Principal Component Analysis (PCA)
Our consultants are competent in performing machine learning tasks in a wide range of software environment such as R, Matlab, Weka, Rapid/Miner, KMINE, SAS Enterprise Miner, IBM SPSS Modeler etc.
Data Visualization is a way to communicate models and ideas that can have a strong influence on business outcomes. Graphics make shapes and trends visible which lead to a mental model and foster better recall. Especially with interactive visualizations one can develop a deeper understanding of underlying models and dynamic behavior. The idea is to visualize data and create insight which can then lead to better decisions.
Immense volumes of valuable data are rapidly piling up. Organizations need ways to more easily interpret and take action on it. Static data tables and charts are dead. People need visual storytelling to more quickly gain insights in a simple and meaningful way. When you can make the data tell a visual story it becomes intuitive and engaging. Effective data visualization of your data provides actionable information for informed, forward-looking business decisions. The benefits of data visualization include but not limited to:
• faster path to answers
• unexpected discoveries
• improved business understanding
• increased return on analytics
• increased analytics maturity
• improved resource prioritization and utilization
Our consultants are available to provide you with assistance in the use of graphics and visualization packages, the development of custom computer graphics tools, the application of graphics algorithms, and the conversion of data into effective graphical representations.
The goal of our graphics consultants is to make the production of scientific visualizations as effective and straightforward as possible. It is often helpful to discuss your project with a consultant and together define a connection between the underlying phenomena and a feasible visual display which effectively communicates it. The consultants may help familiarize you with appropriate software or specific techniques and provide information on computer graphics principles and algorithms. Our consultants can help you with production of images or animations for use in the classroom, at workshops or conferences, for delivery on the web, or for publication, and with conversion of file formats, processing of image or model files. Our consultants are all well competent in writing scripts or graphics programs, and taking on an active role of collaboration by working on long term projects which have a graphics component.
By turning data into visuals, we can help you discover trends and gain valuable insights. We have extensive experience and reputation of creating many beautiful and powerful data visualizations for clients from diverse disciplines including computer science, statistics, machine learning, NLP, and social science.
Our data visualization consultants primarily use the tools like Python, R, Javascript, SQL/Redis, D3.js, infovis (data visualization), Qlikview, Spotfire and Tableau for making your data to speak through graphics.
Econometrics involve the formulation of mathematical models to represent real-world economic systems, whether the whole economy, or an industry, or an individual business. Econometric modeling is used to analyze complex market trends (the demand function) to determine the variables driving the growth or shrinkage of demand for a product or service. Econometric models are used to decipher the economic forces that affect supply and costs (the supply function) within an industry.
Times-series analysis, cross-sectional time-series analysis, structural-equation modeling, input-output analysis, Markov-chain analysis, and multiple regression are some of the techniques used in econometric modeling. Many other statistical and mathematical tools are employed as well, depending on the nature of the econometric task, in the development of econometric models.
Time Series Analysis and Forecasting is an area of Statistics dedicated to the study of observations that present time or space dependence. Analyzing Time Series appears in different fields, such as: Finance, Marketing, Insurance, Meteorology, Hydrology, Economics, Political Science, Energy, etc.
Our experienced consultants can be your best choice to seek help for your econometric modeling and time series analysis problems. Our experts are capable of providing you econometric and time series analysis solution through every analysis software available in common use.
We can assist you with econometric analysis including but not limited to:
• Specification of an econometric model
• Testing model assumptions
• Estimating econometric models
• Testing hypotheses
• Evaluation of alternative economic policies
• Other econometrics methods / models
We can assist you with time series analysis including but not limited to:
• Univariate and multivariate time series models
• Box-Jenkins methodology
• Structural time series models
• Estimation and forecasting
• Other time series methods/models
Bio statistics/Survival analysis gets its name from the fact that it is often used to look at how long people will live, and to see what influences that. Do women live longer than men? Do people who take aspirin live longer than those who do not? and that sort of thing. But it can be time to any event. We could look at how long prisoners stay in jail, how long patients stay in the hospital, how long couples stay married, or any other variable that is a time. The key reason that we need survival analysis is that these data are often censored. If, for example, we were looking at how long couples stay married, we could select some couples, and follow them over time. But some couples won’t get divorced before we finish our study. Similarly, some patients won’t die during our study, and so on.
We have long working experience with hospitals, government agencies, academic and research institutions, and private corporations on biostatistical analysis or statistical interpretation of biomedical testing. Drawing on a team of highly skilled biostatisticians from an elite group of professors and academic researchers, our bio-statistics consulting offers consultations and expertise on a range of relevant areas to researchers.
These consulting services include assistance with design and analysis of clinical trials, design and analysis of observational studies, design and analysis of surveys, assistance with public databases, sample size and power calculations and data analysis and interpretation.
We have vast experience with the analytic procedures typically used in biostatistics research, such as:
• Kaplan-Meier Life Table Analysis
• Cox Regression
• Structural Equation Modeling (as implemented in MPLUS, AMOS and LISREL)
• Multilevel Linear and Nonlinear Models
• Bayesian Analysis based on Markov Chain Monte Carlo methods
The recent proliferation of online Universities offering PhD degrees (such as NCU, Capella, UoP, etc) has led to the situation of students often being ill-prepared to complete the thesis process without seeking outside assistance from a thesis consultant who is familiar with the specific processes followed at these schools. We help these students to save thousands of dollars in tuition, while graduating months earlier than their peers. Offering thesis help to students is now one of the top priorities of our firm.
Over the past several years, we have helped thousands of masters and doctoral candidates to complete their thesis, with many being offered the opportunity to have their work published in journal articles soon after. We consider ourselves to be teachers and not doers, and our entire thesis consulting process encompasses that mindset. We also work closely with researchers who are in the process of writing or designing a study with the aim of publishing it in a peer-reviewed journal.
Every step of the way, we will remain with you as your dedicated thesis/article consultant, assisting you with all steps of the process, including
Topic selection
Finding the relevant articles for your background research
Developing the literature review
Establishing and operationalizing your hypotheses and research questions
APA editing of your proposal and final dissertation
Quantitative and qualitative data analysis,
Defense Preparation including a Power point Presentation to use at your defense
If your committee is giving you trouble, we will be your teammate.
We provide ongoing support throughout the entire process. We can demonstrate how to interpret the results, provide ample instruction on the methods used (and why) and what the results mean, suggest reading materials for you to greater understand the particular analytical methods used, give you a PowerPoint presentation with the main points of the results, and allow unlimited email and phone support to ensure that you completely understand the results of the analysis and can discuss them freely. This includes preparation for the defense and peer review process.
The survey process has many distinct parts, several of which require statistical or psychometric analysis. Our team can assist with all of the quantitative parts of the survey research process, including specifying the initial survey, developing the sampling plan, conducting psychometric tests for reliability, validity, and power, and analyzing the data from the responses.
Our survey development process begins with a consultation to understand the constructs you are interested in measuring. We work with you to operationalize your variables and constructs for future analysis, and to make choices such as whether or not to use open-ended or free-response questions, or using a Likert scale versus other options. We can also analyze data from a pilot study to test for preliminary reliability and validity of the instrument.
Once the responses to the survey have been received, we can conduct the statistical analysis based on the pre-determined methodology. We provide high quality survey data analysis services to help you uncover significant findings within our survey data and illustrate those findings through a wide range of charts and tables, which can be easily understood and interpreted. One of our key commitments is to analyze your results and break the results into meaningful segments that can be used as the basis for key decisions. We understand that every individual has different requirements and different objectives to fulfill that need. In the past we have worked with scholars and researchers from different areas and we had the opportunity to offer consultation services on many aspects of survey data analysis. Our team of data analyst and statisticians can help you in analyzing any survey. We are familiar with all of the standard quantitative methods most commonly used in evaluating the responses from survey research. We are also experienced in qualitative analysis, and therefore can explore themes in open-ended research questions, frequently utilizing the qualitative analysis package Nvivo, ATLAS etc.
We are very familiar with the leading online survey tools, including SurveyMonkey, Zoomerang etc.. If you are using either of these tools, we can help via inputting the survey into the tool for you, or downloading and collating the data outputs. If you are unsure of which survey tool to use, we can suggest which would be best for your particular study, and can do all of the back-office work for you.
We provide survey help with the following services:
Assistance with choosing and justifying the appropriate survey instrument
Assistance with the IRB approval process
Helping administer the survey instrument online using a popular survey system such as SurveyMonkey, Zoomerang etc.
Helping identify target demographics and formulating a participant population
Assessing reliability for your sample or population
Scoring and interpretation
Collecting the data
Cleaning the data
Creating the composite scores
Providing help in selecting the appropriate statistics
Examining the assumptions of the statistics
Interpreting the findings
Creating tables and figures that describe the findings
Explaining the findings so that the graduate researcher can write-up the summary and recommendations
Ongoing support for the results and research defense preparation.
Statistics & Applied Economics Consulting offers a broad scope of services. One of these services is automation of tasks, development of add-ons and applications hosted inside the Microsoft Office Applications that include Excel, Word, PowerPoint, Outlook and Access Database.
The applications run within the MS Office Applications and can be developed to work with other MS Office Application for complete business data analysis and reporting.
Please email us at msoffice.appsdevt@statisticseco.com for enquiries on this service.