Research Methods: Online Surveys and Interviews

In a regression analysis, the variable that is being predicted or explained. It's the 'outcome' variable we are trying to understand.

In regression analysis, these are the variables that are used to explain or predict the dependent variable. They are the potential 'causes' or 'influencers' of the outcome.

A statistical technique used for examining the relationship between two categorical variables. It's often used to see how often different categories occur together.

A statistical test used to compare the mean of two groups where one variable is categorical and the other is continuous. It's used to determine if there's a significant difference in the means of the two groups.

A type of research where data is collected directly from individuals by asking questions.

A type of research where information is gathered by observing individuals or situations. It doesn't involve directly asking questions.

Qualitative research methods are most useful for understanding "why" something happens, exploring motivations and reasons behind actions and behaviors.

One way to address concerns about deception in research is to debrief participants after data collection. This involves providing them with detailed information about the study's purpose, methods, and any withholding of information.

Personal interviews are face-to-face conversations used to gather detailed information from respondents. They offer high sampling control, flexibility, and allow for rich data collection, but they are time-consuming and expensive.

Online surveys are administered through websites or other online platforms. They offer flexibility, visuals, and quick, inexpensive data collection, but response rates can be low.

Online surveys can be improved by keeping them short, optimizing for mobile devices, using simple questions, incorporating visuals, and conducting pretesting.

A common way to lessen concerns about disguised research is to inform respondents that the study is "blind" and explain the reasons for this approach.

One way to address ethical concerns in research is to give respondents the option to opt out of participating in the study.

A key characteristic of online surveys is their flexibility, allowing for visual content and complex questions. However, response rates can be low, which poses a limitation to this method.

An error that occurs due to random chance when selecting a sample from a larger population. It can be influenced by the size of the sample.

Errors that occur during the data collection process, such as non-coverage, non-response, or response errors, and also include recording and administrative mistakes.

The failure to include all qualified elements of the defined population in the sampling frame. This can lead to biased results.

Failure to obtain information from some of the sample elements of the population. This can be due to refusal to participate or being unavailable.

Occurs when individuals provide inaccurate responses, either intentionally or unintentionally. This can be due to misunderstanding the questions.

Errors that occur during data editing, coding, or analysis. These can be human errors or due to software malfunctions.

Errors that occur during the administration of the research, such as sample selection or data collection management issues.

The goal in sample surveys is to decrease ________ error, not any one source of error.

Strategies that can increase the likelihood of people completing surveys.

Placing sensitive questions at the beginning can make respondents feel uncomfortable and less likely to continue.

These tasks ensure data quality and consistency for valid analysis.

These steps are essential for preparing the data for analysis.

A pretest helps identify potential issues with your questionnaire before you launch it. This can include things like unclear questions, confusing instructions, and response options that do not adequately capture the range of answers. By identifying these issues early on, you can prevent wasting time and resources on a flawed questionnaire.

Closed-ended questions provide a limited set of responses. These questions are designed to have only one answer and can be structured with scales, checkboxes, or drop-down menus. Two key considerations include ensuring that all possible responses are covered and that the responses are mutually exclusive to avoid any overlap in meaning.

Avoid using complex words or phrases that might confuse respondents. Focus on using simple language that everyone can understand easily. Simple language makes the questionnaire more accessible and increases the likelihood of accurate and reliable responses.

A census involves collecting data from every single member of the population you are studying. It provides a complete picture of the population, but can be very time-consuming and expensive.

A sample is a smaller group of individuals or entities that represents a larger population. It allows researchers to gather information from a manageable subset, making it easier to study a phenomenon. Samples are often used to draw inferences about the entire population.

Probability sampling is considered the preferred approach because it allows researchers to estimate sampling error. This means they can determine the extent to which their results are representative of the population. This enables more accurate inferences about the overall population based on the sample data.

Snowball sampling is a special type of judgment sample that is used to reach specific, hard-to-find populations. It starts by identifying an initial set of individuals with specific characteristics and then asking them to refer other individuals with similar characteristics. This technique is particularly useful when studying niche groups or communities.

Precision refers to how close multiple measurements of the same thing are to each other. Confidence, on the other hand, expresses the certainty with which we can claim that the true value of a population falls within a specific range. Higher confidence levels indicate a greater degree of certainty in the findings.

A statistical technique used to understand the relationship between a set of independent (predictor) variables and a dependent (outcome) variable.

A statistic (R2) used in regression that represents the proportion of variation in the dependent variable that is explained by the independent variables. It essentially reveals how well the model fits the data.

A statistical test to see if the overall model is significant, meaning there's a significant relationship between the independent and dependent variables.

A statistical test comparing observed frequencies of categorical variables to expected frequencies, to check if there is a significant difference between them.

Analysis based on one variable at a time, describing patterns or characteristics of that single variable.

Analysis that examines the relationships between multiple variables, allowing for more complex understanding of data and its patterns.

A statistical test comparing the mean of a sample of continuous data to a known value (population mean or historical mean).

A statistical test that examines the relationship between two categorical variables. It tells you if there is a significant association between the categories of these variables.