Research Methodology - Tools

A plan or framework for a study, guiding data collection and analysis.

Minimizing costs, facilitating smooth operations, and maximizing information gathered with minimal effort, time, and money.

Data analysis must be sufficient to highlight findings and use appropriate methods.

Thoroughly check the accuracy and dependability of collected data.

Research conclusions must be based on the collected data and justified by them.

Research with trustworthy researchers strengthens its confidence level.

To apply research findings from a sample to a broader population.

A plan outlining data collection methods and analysis techniques, keeping in view research objectives, available resources, and staff time.

A well-designed research project ensures smooth operations, minimizes bias, and maximizes the reliability of data.

A poorly designed research project can jeopardize the entire study, leading to unreliable results and wasted resources.

It serves as a roadmap for the research process, outlining essential steps and methods for data collection and analysis.

It helps organize ideas, identify potential flaws, and provides a direction for the research team.

In research design, it refers to the unbiased and accurate measurement of data, regardless of who collects or analyzes it.

A research design should use data collection methods that are objective and free from any personal biases or influences.

A good research design aims to minimize errors and biases in the data collection and analysis process, leading to more accurate results.

It incorporates objectivity, reliability, validity, and generalizability to ensure accurate and meaningful findings.

A statement proposing no difference or relationship between variables. It's a starting point for testing if a finding is statistically significant.

A statement proposing a specific relationship or difference between variables, often based on prior research or theory. It's what we're trying to prove.

It allows us to use statistical tests to determine if the observed differences or relationships are likely due to chance or a real effect.

When statistical analysis shows the null hypothesis is very unlikely to be true, we reject it. This supports the research hypothesis.

A type of null hypothesis that doesn't specify the direction of the relationship or difference.

It guides data collection, analysis, and conclusion drawing, ensuring the research effectively addresses the question.

The process of creating a testable hypothesis based on existing knowledge and theory.

Can lead to inadequate data, flawed conclusions, and difficulty applying statistical analysis.

It acts as a roadmap for the research process, directing the researcher towards specific observations and data.

They help evaluate the probability of observing the research findings if the null hypothesis were true, aiding in its acceptance or rejection.

A sample that accurately reflects the characteristics of the entire population it is drawn from.

A systematic error in the sampling process that leads to a sample that is not representative of the population.

A sampling method where personal opinions or biases do not influence the selection of participants.

A sampling method that minimizes errors and provides reliable estimates about the population.

A sample that covers all important aspects or characteristics of the population.

The process of selecting a representative subset of individuals from a population to study their behavior and draw conclusions about the entire group.

Less common than in behavioral research, where studying a small group can provide insights about a larger population.

It makes research more economical and accurate by allowing researchers to study a smaller group while still getting reliable information about the whole population.

The idea that despite being different, individuals within a population share common traits that allow for representative sampling.

The ability to choose a sample that accurately reflects the characteristics of the entire population.

While absolute accuracy is impossible, relative accuracy is crucial for reliable conclusions about the population.

A miniature representation of an entire group, like a small picture representing a larger scene.

Samples provide a cost-effective and efficient way to understand a population's characteristics without studying every individual.

To draw accurate inferences about the characteristics of a population by observing the traits of a carefully chosen sample.