Statistical analysis is the main method in a doctoral dissertation or thesis. The collected data must reorganize with the help of analytical skills to evaluate the results obtained from the investigation or experimentation. Statistical analysis involves the following: data collection, data analysis, and data evaluation. Our academic writers are expert in the statistical analysis works from scratch to an end i.e., from tools development to the analysis and evaluation of obtained data as well as maintains professionalism in the data presentation.
PhD Assistance helps the doctoral candidates for the master thesis tools development involving questionnaires and makes use of the statistical software like PLS LISTERS, AMOS, SPSS, and SAS. PhD Assistance provides advanced training courses with the provision of video conferences to the scholars. Our experts not only develop the statistical analysis but also help to clarify the queries you have, provide guidance in problem-solving, and discuss with you for a better understanding of statistical analysis.
SERVICES WE PROVIDE ON PHD STATISTICS
Only the Statistical analysis from the shared raw data. We perform data analysis with the help of relevant statistical tools and paste the results
Along with the basic service, we provide the key explanation without discussions against the Literature review
We perform data analysis with the help of relevant statistical tools and do formatting according to the style of the manuscript logically. We provide the explanation along with discussions for the statistical analysis with the help of a Literature review of the relatable studies
WHEN YOU ORDER FOR STATISTICAL ANALYSIS, PHD ASSISTANCE PERFORMS THE FOLLOWING
Compilation and recoding of data:
- Creation of Data entry in excel format
- Data exportation to statistical software like SPSS.
- Normality Checking and labeling.
- Rectifying the errors in data entry or any missing data.
- Checking outliers with the help of relevant analysis methods.
Assistance of Statistical data analysis:
Although there exist many methods in data analysis, customary format initiates from descriptive statistics (standard deviation, range, minimum, mean, maximum, confidence interval, standard error) for the variables involving in the socio-demographics such as sex, income, marital status, occupation, etc.,).and then reliability checking for the results obtained. Additionally, hypothesis testing is performed with the help of relevant statistical tools in writing assignments
Statistical output interpretation:
Ph.D. Assistance helps you in data interpretation pertinent to the thesis and assures a complete understanding of the output. We also provide statistical assistance to clarify your doubts.
Figures and Tables presentation:
PhD Assistance presents you the statistical output of the thesis as per the format of journals along with relevant interpretation quantitatively and qualitatively and also includes comments on the research methodology, limitations, and strengths. On this basis, PhD Assistance guides your research work especially in the statistical analysis section [For instance design of the study, sample size, questionnaire validity and reliability, and response rate, etc.,] We also provide tutoring in the section of statistical analysis that gives high reliance in defending your dissertation methodology.
WE VERIFY THESE CHECKLISTS BEFORE THE PROJECT DISPATCH
- The procedures of data analysis described are adequate and adequately detailed for the replication of the study.
- The procedures of data analysis satisfy the research design; theory, models, or hypotheses operates the analysis of data.
- The data whether fulfilled the assumptions on the statistical use such as distributions normality and data’s measurement properties.
- Check whether the statistical test results are optimal (appropriate).
- Apply formal adjustment in the levels of significance if there are many comparisons or tests involved in the statistical analysis.
- Consideration of power issues in the study of statistical analysis that involves small sample sizes.
- Fulfill the primary needs of data validity, reliability, trustworthiness, validity, and bias absence in the qualitative research depends on words rather than numbers.
Statistical Analysis report
- Consider the assumptions on the statistical use.
- The statistical reports are appropriate and correct.
- Analyses count is relevant.
- Functional significance measures such as variance proportion or size of the effect for the analysis of hypotheses test.
- Results are presented in an easily understandable manner.
- Results are efficient and contextualized.
- Results are presented completely.
- The data presented is relevant and adequate.
- Figures, graphs, or tables are sensibly provided.