Quantitative Research Support
Quantitative data means the numerical text or data related to the research. It is usually practical-based data, which requires inference, calculation and interpretation. This type of data requires special analysis and thorough proofreading and editing. It involves an approach of collecting, analyzing and calculating numerical data related to the research topic.
Purpose and goal
Quantitative data aims at measuring variables or numerical data and analysing the relationship between them by using appropriate quantitative methodology. It helps in reducing bias and flaws by observing and measuring the data of the research text.
Research design
Quantitative research starts with a research question often hypothetical in nature. Researchers use various sampling techniques and procedures suiting the particular research. Data is collected through surveys, experiments, etc.
Variables
It involves both dependent as well as independent types of numerical data. These data are controlled by researchers as per the requirements.
How to conduct quantitative research of data?
There are various steps to conduct quantitative research of data. These steps are:
Define research objective : The objective of conducting the research should be explained in the paper. This helps in conducting the research process smoothly and without any confusion.
Literature review : A thorough review of the content needs to be conducted. This helps in understanding the already existing research. It helps in the identification of gaps and shortcomings in the research.
Design the study : The author should appropriately design the study. Common study designs include experimental, correlational, cross-sectional, etc.
Participants selection : A sample must be selected from the targetted audience as representatives of the audience. There are various factors to be considered while selecting the participants, such as sample size, sampling method, etc.
Data collection : The data must be collected using structured methods appropriate for the research. There are various methods used for data collection, such as surveys, experiments, etc. The data collected must be relevant and reliable.
Data cleaning : They must be clean and appropriate. It must be complete, and consistent and must have integrity and accuracy.
Data analysis : Choosing appropriate techniques, statistics and methods for analysing data accuracy is highly important.
Interpret results : While interpreting the results of data, statistical analysis must be done with great precision and focus. It must be noted whether the result interpretation is in favour of the research question or not.
Challenges faced while conducting quantitative research
Quantitative research is a challenging process. Researchers often encounter many challenges and difficulties. These challenges are
Sampling issues
Obtaining the targeted samples can be very challenging. Researchers may face many difficulties in finding adequate samples.
Invalid measurement
It is difficult to find samples with valid measurements. This challenges the reliability of data.
Data collection challenges
The collection of quantitative data requires time and intensive resources. Researchers may find it difficult to reach the participants, conduct the survey, etc.
Complex statistics
Statistical analysis becomes difficult for students to conduct. It gets challenging for the researchers to select appropriate tests.
Interpreting results
Often the data and variables are complex. This interpretation is challenging. Researchers need to ensure that the results of the research are interpreted accurately.
Limited resources
Resources such as funding, time, access to data expertise in methodology, etc. are limited to students. They fail to overcome these challenges and hurdles.
The methods for conducting quantitative research
PhD research involves various techniques and quantitative methodology. Here are some of the common methods of quantitative research:
Experimental studies
Quantitative research includes studies involving experiments to manipulate independent variables and measures affecting dependent variables.
Surveying
It involves conducting surveys to collect quantitative data from participants. Surveys can be flexible as per the requirements of the research question.
Correlational studies
It involves an examination of variables through correlational analysis. Common techniques used are Pearson’s correlation coefficient and Spearman’s rank correlation.
Regression analysis
It uses regression models to analyse the relationship between different types of variables. It is used to predict outcomes and identify significant predictions.
Meta-analysis
It is used to analyse quantitative data from multiple studies. It helps in examining overall effects, trends and patterns. It combines statistical results from individual studies to conclude
Factor analysis
It helps in exploring factors within a set of variables. Factor analysis includes various techniques like exploratory factor analysis (EFA), and confirmatory factor analysis (CFA).
Time series analysis
Quantitative analysis includes data collected over time. To identify trends, patterns, seasonality and relationships between variables.
PhDFY helps its clients in quantitative research in various ways
The advantages students get on collaborating with PhDFY are many in number. Our outstanding services help them achieve their academic goals. We help our clients by:
Clear research objective
PhDFY offers well-defined and specific research objectives that help the readers as a guide for the entire research project. We make sure the data has an objective, is measurable and suitable for the research question.
Data-driven techniques
We have a team of highly capable researchers who make data-driven decision-making.
Data analysis
We help in analysing the data. Our experienced analysts go through every single data entry in the text to make sure it is accurate and reliable.
Standardized procedures
We use standardized procedures and methods for data interpretation and collection. We provide services efficient in terms of data collection, analysis and interpretation.
Accurate result
We use highly advanced tools and techniques to check the accuracy of the numerical data. Often PhD students lack the skills and knowledge to conduct quantitative research, PhDFY helps such students in their work.
Why PhD students choose us?
PhDFY, established in 2009, has become a very reliable and highly trusted brand in the market. Students trust us for their writing and research work. Our team consists of highly experienced academic scholars who hold doctorate/PhD degrees and highly experienced experts. We have all the required legal registrations and certificates from esteemed platforms. Our work has received appreciation and recognition eminent by institutions and organizations. We have a record of 100% accurate and reliable service. Our 24*7 customer support and transparent pricing policy have won the trust of our clients. We are proud of our customer return rate and how our work has been proven to contribute to our clients’ careers and overall academics.
Quantitative research usually requires high-cost procedures and techniques of data collection and analysis. PhDFY uses advanced techniques and tools, with the help of our experts we frame a very budget-friendly pricing policy, without compromising the work quality. Students often fear getting caught and being blamed for plagiarism and academic fraud. PhDFY ensures 100% confidentiality and secrecy to their clients. We never disclose their identities without their consent. Our work is free from any kind of plagiarism. We use intensive research methods and techniques to conduct our work. This helps in making our work highly dependable and trustworthy.