Private tutor in Houston, TX
Master of Arts, University of South Florida, Tampa, FL, Clinical Psychology Bachelor of Arts, Magna Cum Laude, University of St. Thomas, Houston, TX, Certified Six Sigma Black Belt, ASQ, June 2013
DISSERTATIONS, (Ph.D., Psy.D. DNP and more), THESIS (All Master Level Final projects), and STATISTICAL, RESEARCH Design and Method CONSULTATION and TUTORING WHAT MAKES my services EXCEPTIONAL? DISSERTATIONS and THESIS It's time……….You need to start writing your Dissertation or Thesis; you know this. Still, knowing and doing are two very different states, and I understand that getting your dissertation's Introduction chapter going can be the most challenging aspect of the entire writing process. And it's not just you; writers as a whole have struggled with this very problem for the longest of times, namely: How do I begin? I can help through all the paper sections and processes that a dissertation or thesis candidate goes through! Chapter 1: Introduction In this case, the Introduction to your dissertation aims to firmly ground an unfamiliar reader in your research topic, developing enough interest along the way such that your audience actually wants to read the rest. I can help you understand what each section needs and how to develop your sections: Statement of the Problem wherein you begin drilling into the specific issue you will investigate. Purpose of the Study follows, which comprises a few sentences that summarize the motivating rationale behind the study. Significance of the Study as it pertains to these same readers and contextualizes your specific research problem—which strictly applies to the research community and experts in the field—by speaking more broadly to the general problem that affects the community at large. Research Design piece translates the statement of the problem into specific research questions. Nature of the Study section, serves to connect your research to more than just itself. In this section we identify the Theoretical / Conceptual Framework that then connects your research study to other research by providing a perspective for interpretation and comparison. You can also juxtapose this section with your Definition of Terms, which includes all constructs and variables investigated in the study, including the characteristics of the sample and operationalized terms. Assumptions, Limitations, and Delimitations section starts by identifying any condition that gets taken for granted in research. Chapter 2: Literature Review Your Literature Review chapter represents an integral component to your successfully completing your dissertation. This is because, after the Literature Review's introduction—which orients the reader as to the purpose of the topic and states the main points clearly—this chapter provides the conceptual basis, justification, analysis, and interpretation of the problem under investigation. It does this by presenting: (1) the historical knowledge in the field; (2) knowledge of similar research; (3) knowledge pertaining to unsolved problems surrounding your topic; and (4) any knowledge of gaps in the literature. Perhaps just as important, your Literature Review will also cite the research that you used to develop key elements of your study. Chapter 3: Method Research Question and Hypotheses Development After selecting your dissertation topic, you need to nail down your research questions. Importantly, whether your study utilizes a quantitative or qualitative approach, research questions need to be at least two things: interesting and researchable. Your questions need to be researchable if you can confirm that the data are readily available to you, that the constructs can be operationalized into variables, and that the topic is manageable in size. Research Design and Methods Essentially, the research plan is an abbreviated introduction and methodology chapters. In an introduction, the researcher states: the purpose of the study and how the study examines the research problem; the significance of the study, which should explain why this study is important; and the study's research questions, which sit at the heart of the What that the study seeks to examine. Additionally, the research plan addresses the approach of the study, which is either qualitative or quantitative, the research design, the methodological model, and the rationale of the study. Chapter 4: Results Database Management and Development SPSS is the abbreviation of Statistical Package for Social Sciences and it is used by researchers to perform statistical analysis. As the name suggests, SPSS statistics software is used to perform only statistical operations. I am an expert in SPSS software and statistical operations. If you are a graduate student or researcher, I can assist you in the following areas: • Understanding the capabilities of SPSS software • Cleaning, coding and data entry in SPSS • Choosing the correct statistical test to run • Interpreting SPSS output • Statistical analysis of SPSS data output Statistical Analysis and Results Section The data analysis plan refers to determining how the data will be cleaned, transformed, and analyzed. Cleaning the Data is the removing of univariate and multivariate outliers, dealing with missing data, and assessing for normality. Missing data is the absence of an observation on a variable. There are a few remedies: drop the observation with the missing data, mean substitution, and multiple imputation (using SPSS or EQS). Normality refers to the shape of the distribution of scores (e.g., shape of a normal bell curve). Transforming the Data for when the data is not normally distributed a transformation of the data can be appropriate. Some common transformations are the square root, logarithmic, and inverse. Analyzing the Data is based on two things: the way the hypothesis is stated in statistical language and the level of measurement of the variable. The Hypothesis is the way the researcher states the hypothesis makes a difference in the data analysis. Level of Measurement of the Variables is a key factor in selecting the correct data analysis. I offer the following services: 1. Edit your research questions and null/alternative hypotheses 2. Edit data analysis plan; specify specific statistics to address the research questions, the assumptions of the statistics, and justify why they are the appropriate statistics; provide references 3. Justify your sample size/power analysis, provide references 4. Explain your data analysis plan to you so you are comfortable and confident. Chapter 5: Discussion While your dissertation's Discussion Chapter has been years in the making—you have arguably been working toward it your entire life—now is certainly not the time to relax. Even though all of the so-called "hard" work may be in the past, those who have not mentored you through the entire research process may not care to review the entirety of your manuscript. However, for the many readers who approach your study post-publication, your Discussion Chapter may very well be the only chapter they read. Discussion Chapter must provide an explanation of your contribution to the body of knowledge in your field, yet it needs to do so by offering a compact review of your dissertation as a whole. A Summary of Chapters 1 and 3 is where you reiterate the essential points from both Chapters. Next, you will need to provide a summary of your study and what it encompassed, including your findings and conclusions. Interpretation is discussing your results, always as they relate to the literature, as well as a section on the limitations of your results. Thoroughly addressing these sections solidifies your position in your readers' eyes as the expert. The end of the Discussion Chapter provides you with a place to help guide future efforts that emanate from what you are now polishing. Finally, once you have all of these pieces assembled, you will need to elegantly compose a conclusion section to your Discussion Chapter that includes an overview of the chapter and your research findings. The Internal Review Board Process So, you've done your research, and you've found a gap in the literature that needs to be addressed. Even more impressively, you have designed a study that can fill this gap. So what do you do now? The obvious answer is to actually conduct your study, but before that can happen you have to overcome the roadblock of attaining Institutional Review Board (IRB) clearance. To put it simply, the purpose of the IRB proposal is to answer four key questions of why your research is important, how you intend to conduct the research, who will take part in your study, and how you will manage experimental data once you have collected it. Statistics Tutoring Individual Tutoring Individual tutoring provides you with an introduction to the basic methods of collecting, organizing, and analyzing psychological data. YOU will learn a variety of descriptive and inferential statistical techniques. The inferential techniques include an emphasis on statistical inference (e.g., t tests, F tests, and selected non-parametric statistics). Statistical Analysis I conduct many different parametric and non-parametric statistical analyses to meet your needs. Below is a list of some of the analyses I provide. Please note this is not an exhaustive list by any means! • ANOVA (Analysis of Variance) all types • ANCOVA all types. • Regression (multiple, logistic, ordinal, hierarchical and more) • Bivariate Correlation • Chi-Square • t-tests • Discriminate Analysis • Factor Analysis • MANOVA (Multivariate Analysis of Variance) • MANCOVA (Multivariate Analysis of Covariance) • Reliability Analysis • Structural Equation Modelling • Test for Moderation and or Mediation Training for Six Sigma Certification Six Sigma Certification Training for Black, Green, and Yellow Belt Candidates! I am a Certified Lean Six Sigma Black Belt and can help you prepare for your test! I use the DMAIC project methodology which has five phases. I will take you through the methodology and help you learn to understand and apply it: 1. Define the problem, the voice of the customer, and the project goals, specifically. 2. Measure key aspects of the current process and collect relevant data. 3. Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out root cause of the defect under investigation. 4. Improve or optimize the current process based upon data analysis using techniques such as design of experiments or mistake proofing, and standard work to create a new, future state process. Set up pilot runs to establish process capability. 5. Control the future state process to ensure that any deviations from target are corrected before they result in defects. Implement control systems such as statistical process control production boards, visual workplaces, and continuously monitor the process. Six Sigma Certifications Black Belt - A specific Six Sigma term to describe a team leader and one who has achieved accredited 'Black Belt' qualification via an appropriate training course. Green Belt - A Six Sigma team member, who has received Green Belt training, works part-time on Six Sigma projects under the guidance of a Black belt team leader. Statistical Programs Need Help with Understanding stats programs with use of data, results, output, databases, and more? SPSS - Statistical Package for Social Sciences SPSS is a comprehensive statistical package with substantial programming and data-transformation features. I can assist you with the following: • Programming (e.g., computation, recodes, conditional execution and looping) • Statistical analysis (e.g., descriptive statistics, tables, regression, t-test, ANOVA, factor analysis, logistic regression and time series) • Graphics (e.g., histogram, pie chart, scatter plot, line graph, and 3-D plots) • Utilities (e.g., sorting, merging and table lookup, transposition and displaying the dictionary for an SPSS system file) • Spreadsheet appearance: Using interactive graphical SPSS, data are displayed in a matrix similar to a spreadsheet. Data may be entered directly in this window or read from a file. RESEARCH I establish and operationalize your hypotheses and research questions providing ample instruction on the methods used providing assistance crafting and creating your methodology section inputting, organizing, and cleaning the data implementing the statistical analyses testing reliability (such as Cronbach's alpha, test-retest reliability, split-half reliability, and inter-rater reliability) and validity (such as content validity, construct validity, criterion validity, internal validity, and external validity) writing up all results, including APA tables and figures providing syntax and raw output file explaining the results so you can write the discussion section and defend them conducting two rounds of incidental statistics (i.e., if you or committee would like additional statistics) performing qualitative analysis providing expert editing services to you assisting you seeking dissertation writing help with your introduction and discussion chapters offering comprehensive dissertation writing help to you seeking creation or enhancement of your literature reviews preparing an effective PowerPoint Presentation supporting you until the project is complete DATA MANAGEMENT I am dedicated to detecting and correcting corrupt or inaccurate records from a record set, table, or database. The process of data cleaning includes data auditing, work flow specification, work flow execution, post-processing, and controlling. I use popular methods. Those include parsing, data transformation, duplicate elimination, and statistical methods. By analyzing the data using the values of mean, standard deviation, range, and clustering algorithms, we can find values that are unexpected and thus erroneous. I can examine any standardized residual greater than about 3 in absolute value, Hat element greater than 3p/n (p=k+1, k degrees of freedom), a Cook's distance > 1, and Mahalanobis's distance for case. We run Outlier Analysis such as a run-sequence plot, a scatter plot, a histogram, and a box plot. TESTS FOR RELIABILITY, VALIDITY, AND POWER I can test reliability (such as Cronbach's alpha, test-retest reliability, split-half reliability, and inter-rater reliability) and validity (such as content validity, construct validity, criterion validity, internal validity, and external validity). STATISTICAL ANALYSIS I can design and perform the required statistical analyses. We are experts in statistical analysis such as t-test, ANOVA, traditional regression, logistic regression, MANCOVA, factor analysis, cluster analysis, survival analysis, time series analysis, canonical correlations, discriminant analysis, and more advanced statistical techniques such as structural equation modeling (SEM), hierarchical linear modeling (HLM), and path analysis. We are experts in statistical programming languages such as SPSS. METHODOLOGICAL DESIGN “Methodology” implies more than simply the methods you intend to use to collect data. It is often necessary to include a consideration of the concepts and theories which underlie the methods. For instance, if you intend to highlight a specific feature of a sociological theory or test an algorithm for some aspect of information retrieval, or test the validity of a particular system, you have to show that you understand the underlying concepts of the methodology. When you describe your methods it is necessary to state how you have addressed the research questions and/or hypotheses. The methods should be described in enough detail for the study to be replicated, or at least repeated in a similar way in another situation. Every stage should be explained and justified with clear reasons for the choice of your particular methods and materials. Experimental Analysis. The simple two-group posttest-only randomized experiment is usually analyzed with the simple t-test or one-way ANOVA. The factorial experimental designs are usually analyzed with the Analysis of Variance (ANOVA) Model. Randomized Block Designs use a special form of ANOVA blocking model that uses dummy-coded variables to represent the blocks. The Analysis of Covariance Experimental Design uses, not surprisingly, the Analysis of Covariance statistical model. Quasi-Experimental Analysis. The quasi-experimental designs differ from the experimental ones in that they don't use random assignment to assign units (e.g., people) to program groups. The lack of random assignment in these designs tends to complicate their analysis considerably. For example, to analyze the Nonequivalent Groups Design (NEGD) we have to adjust the pretest scores for measurement error in what is often called a Reliability-Corrected Analysis of Covariance model. In the Regression-Discontinuity Design, we need to be especially concerned about curvilinearity and model misspecification. Consequently, we tend to use a conservative analysis approach that is based on polynomial regression that starts by overfitting the likely true function and then reducing the model based on the results. The Regression Point Displacement Design has only a single treated unit. Nevertheless, the analysis of the RPD design is based directly on the traditional ANCOVA model. When you've investigated these various analytic models, you'll see that they all come from the same family -- theGeneral Linear Model. An understanding of that model will go a long way to introducing you to the intricacies of data analysis in applied and social research contexts. There are many different ways to approach the research that fulfills the requirements of a dissertation. These may vary both within and between disciplines. It is important to consider the expectations and possibilities concerning research in your own field. You can do this by talking to your tutors and looking at dissertations written by former students on your course. QUANTITATIVE as well as QUALITATIVE ANALYSIS I consult helping students and professors design research methodologies and analyze the qualitative data. I am dedicated to understanding the needs and desires of people. APA FORMATTED REPORT WRITING I use The sixth edition of the “Publication Manual of the American Psychological Association” directs you how to format and structure your research proposal. This is the most common style used for proposal related to the social sciences. A research proposal in APA format should include a title, abstract, main body and references. Student Reviews "I have been working with Brian since 2013. In that time, Brian's statistical knowledge and skill at teaching has allowed me to pass all my exams and tests as part of my PhD. Simply put, without Bryan's help, I would not have been able to progress with my PhD, simple as that. Being a mature student and not having looked at statistics for several decades, having Brian's patient and effective coaching gave me the confidence to tackle what would have been an impossible subject to pass. And not only did I pass, but I attained a GPA of 4.0 with straight A's in all of my courses." "Don't bother looking at the competition. Period. There's no one who comes close. You won't regret making the decision to work with Brian - for me, it was one of the best academic decisions I've ever made." "Brian Is very easy to work with he takes the time required to help you fully understand the problem at hand. He is very knowledgeable and is extremely good at working through a problem in such a way that you are the one actually solving the problem with a few pointers from Bryan to keep you going in the right direction. I would recommend Brian to any student needing additional assistance." "I was very lost in my class and did not totally understand what the instructor was requiring for my research paper. I found Bryan and my anxiety in the class dramatically decreased. "Brian is patient and explains the process in a manner that I can understand. I love all the tools that he utilizes and it helps me to connect the pieces." I was ready to quit my Master’s program but with Brian's guidance I now feel confident enough that I can continue in the program. I have already registered for my next research class which begins next month and have informed Bryan that I will once again need his expertise. "If you are looking for a tutor that has flexible hours, patient, knowledgeable and worth his fees. Brian is your guy." "Brian is very supportive, and patience. He is always available when you need his expertise in the areas of statistics and your thesis and or dissertation research. I highly recommend him." "Working with Brian was a fantastic experience. His background really helped to connect with where I was coming from. From helping to make sure I understood basic to more complex statistical concepts, to offering feedback through my dissertation process - it was a joy to work with him. He's very capable, flexible and easy to communicate with!"
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I am an Accredited Member of the American Statistical Association, Certified Lean Six Sigma BB, an IASSC Certified Six Sigma Trainer.
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