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| Key point | Research method | Research methodology |
| Definition | Research method is a way or plan that researchers use to find answers to questions or solve problems. | Research methodology is overall strategy or framework guiding the research process, how the they collect and analyze information to learn new things. |
| Nature | To cover the practical aspects of conducting research, such as data collection tools and statistical analysis methods. | To covers the philosophical, theoretical, and conceptual bases that influence how research is conducted. |
| Purpose | To Collect information and answer research questions. | To make a roadmap of hold process |
| User | Its use researcher to study’s objective and research design. | Its use Researchers, scholars and academy to design, execute, and evaluate research studies. |
| Formality | Its process to informal guide line to complete frame work | Its process to formal guide line to complete framework. |
| Key point | census survey | sample survey |
| Definition | A census survey collects data from every individual or unit in a population. | A sample survey collects data from a subset, or sample, of the population.
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| Nature | Collect information of all population. | Collect information of selected sample |
| Purpose | Provide actual picture of all population. | Provide actual data of selected population. |
| User | Its use properly at Governments, organizations and institutions. | Its use properly at researcher, marketer and scientism |
| Formality | highly formal and structured. | low formal and structured. |
| Key point | Population research | sample research |
Definition | Collects data from every individual or unit in a population. | A sample survey collects data from a subset, or sample, of the population. |
| Nature | Collect information of all population. | Collect information of selected sample |
| Purpose | Provide actual picture of all population. | Provide actual data of selected population. |
| User | Its use properly at Governments, organizations and institutions. | Its use properly at researcher, marketer and scientism |
| Formality | highly formal and structured. | low formal and structured. |
| Key point | descriptive research | analytical research |
| Definition | It’s like describing what you see around you | It’s like trying to figure out why things happen |
| Nature | Simple observation.
| Investigating deeper |
| Purpose | To tell us what’s happening. | To understand the reasons behind things |
| User | People looking to see patterns or situations | People trying to solve problems |
| Formality | More like everyday observations, not too strict | Needs a clear plan and careful steps |
| Key point | Data | Information |
| Definition | Raw facts and figures, like numbers or measurements is called data. | Process data is called information |
| Nature | Unorganized and unprocessed.
| Organized and meaningful. |
| Purpose | To be collected and analyzed. | To make decisions or understand something better. |
| User | Researchers, scientists, or anyone collecting raw details. | Businesses, students, or anyone who needs process data. |
| Formality | Just raw, no specific format. | Process and specific format. |
| Key point | exploratory | descriptive |
Definition | It’s like being a detective at the start of a case | It’s like describing what you see around you |
| Nature | It’s all about exploring without a fixed direction. | Simple observation. |
| Purpose | To find out what’s going on when you’re not sure. | To tell us what’s happening. |
| User | People who are just starting to look into a new topic or problem | People looking to see patterns or situations |
| Formality | Not too strict. It’s more about gathering initial ideas and insights. | More like everyday observations, not too strict |
| Key point | Basic research | Applied research |
| Definition | It’s like learning just to satisfy your curiosity. | This is like inventing a new tool to fix a specific problem. |
| Nature | Very open and general. | Targeted and practical. |
| Purpose | To discover new things without thinking about solving a specific problem. | To create solutions or improve how things work. |
| User | Scientists and researchers who are exploring fundamental concepts | Companies, engineers, and professionals looking to address specific challenges. |
| Formality | It can be quite formal with structured methods. | More like everyday observations, not too strict. |
| Key point |
Qualitative research |
Quantitative research |
| Definition | Qualitative research is exploring ideas and experiences in detail. | Quantitative research is numbers to find answers. |
| Nature | Its focus on the actual quality of Question and answer. | Its focus on number of questions and answer. |
| Purpose | To get actual behaviors, feeling and motivation. | To get theoretical test or hypotheses Test of data. |
| User | Researchers studying human behavior, like psychologists, sociologists, and marketers. | Scientists, economists, and researchers who need precise measurements to test ideas. |
| Formality | Its provide less formal structure. | Its provide good formal strure. |
| Key point |
Survey |
Experiments |
| Definition | Gathering information by asking people directly is called survey. | Testing something to see what happen is called experiments. |
| Nature | Direct collect from customer. | Direct result to see effect. |
| Purpose | To understand consumer properly. | To understand result for reuse. |
| User | Businesses, governments, and researchers who want to know about people’s opinions or behaviors. | Scientists and researchers looking to discover or prove cause-and-effect relationships. |
| Formality | It can run on question base. | It can run by structure base. |
| Key point | Cross-sectional | Longitudinal study |
Definition | cross-sectional is like big photo that’s looks every thinks at a moment. | longitudinal study is like series that’s shows change over a long period. |
| Nature | One capture of different thinks | One subject changes at different time |
| Purpose | Gathering current data from various sources. | Gathering data from taking day, month and years. |
| User | Researcher who use quickly | Researcher who use actual changes |
| Formality | Less formal | More formal |
| Key point | Primary data | Secondary data |
| Definition | Raw data collected from survey, interviews and experiment is called primary data. | Collected data as like report, newspaper or books is called secondary data. |
| Nature | Free and original data | Already collected and repurpose |
| Purpose | To get original data from source | To save money & time |
| User | Researcher who find specific data | Researcher who use data so fast. |
| Formality | Good and formal | Less formal |
| Key point | Mean deviation | Standard deviation |
| Definition | Mean deviation tells you the average distance. | Standard deviation gives more weight to bigger differences. |
| Nature | differs from the average | Square the difference |
| Purpose | To get simple idea | To get clear picture of data |
| User | Who get basic data | Who get specific and financial data. |
| Formality | It’s less formal | More formal |
| Key point | Sampling Error | Standard Error |
Definition | Difference between sample and actual data is called sampling error. | Difference between sample mean and population mean is called standard error. |
| Nature | Its show Randomness selecting a sample | Its show sample vary from one to another. |
| Purpose | its provide accuracy of sample estimation | It provides reliability of sample estimation |
| User | Survey designer consider this error | Researchers, statisticians, and analysts consider this error. |
| Formality | Normal or basic familiarity | Standard familiarity |
Differences between technical and popular reports based on five key point are as follows:
| Key point | Technical Report | Popular Report |
| Definition | A technical report is a document that explains detailed information on a specific topic. | A popular report is a document that presents complex information in a simple and clear way for the general public to understand. |
| Nature | This report describe the Process of research. | This report describe the solution & findings. |
| Purpose | It’s make to use professional field. | It’s make to simplify complicated subjects so that anyone can understand them. |
| User | Used this report present information to client and sponsors. | Used this report make to use policy maker of the business. |
| Formality | This report make perfect official & formal. | This report is not perfect official & formal. |
This table highlights some important point of Difference Technical Report and Popular Report.
| Key point | Parametric | Non- parametric |
| Definition | Parametric test is called statistical tests. | Non-parametric test is statistical test but not assumption about the population of distribution. |
| Nature | Numerical data. | distribution-free data |
| Purpose | test relationships between to variables | No relation between two variables |
| User | Researchers and statisticians use parametric tests when data meet the required assumptions. | Researchers, particularly in fields where data may not meet parametric assumptions, employ non-parametric tests. |
| Formality | Parametric tests are considered more formal | Non-parametric tests are less formal |
| Key point | Hypothesis | Null hypothesis |
| Definition | A research hypothesis is an educated guess predicting the relationship between variables or the expected outcome of a study | A null hypothesis is a statement suggesting that there is no significant relationship or effect between variables in a study. |
| Nature | proposing an anticipated result.
| No effect, difference or relationship.
|
| Purpose | test relationships between to variables | No relation between two variables |
| User | Researchers, scientists, and academics create research hypotheses to direct their research. | Researchers and statisticians use null hypotheses to evaluate the significance of research findings. |
| Formality | Research hypotheses are formal, specific. | Null hypotheses are less formal and specific.
|
| Key point | Correlation | Regression |
| Definition | Correlation measures the strength and direction of the relationship between two variables. | Regression predicts the value of one variable based on the value of another variable.
|
| Nature | it indicates how changes in one variable are associated with changes in another variable. | It models the relationship between variables by fitting a line or curve to the data.
|
| Purpose | Correlation helps to understand the extent to which variables are related to each other. | Regression helps to understand how changes in one variable affect another and to make predictions.
|
| User | Researchers, analysts, and scientists use correlation to explore connections between variables. | Researchers, economists, and analysts use regression for predictive modeling and understanding causal relationships. |
| Formality | correlation coefficients ranging from -1 to 1.
| Regression analysis can be more complex. |
| Key point | Proposition | Hypothesis |
| Definition | A proposition is a statement or idea put forward for consideration or discussion.
| A hypothesis is a testable prediction or statement about the relationship between variables in research.
|
| Nature | It can be a claim, assertion, or proposal that may or may not be based on evidence.
| It is based on existing knowledge, theory, or observation and is subject to empirical testing.
|
| Purpose | Propositions aim to express a point of view, persuade, or stimulate further inquiry.
| Hypotheses guide research by proposing expected outcomes or relationships to be investigated.
|
| User | Writers, debaters, and policymakers often use propositions to present arguments or ideas.
| Scientists, researchers, and scholars formulate hypotheses to structure their studies.
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| Formality | Propositions can range from informal statements to formal propositions in debates or legal contexts. | Hypotheses are formal statements that are specific, testable, and often derived from existing theory or empirical evidence. |