Module 1: Managing Databases

A question with a limited set of predetermined choices for the respondent to select from.

A closed-ended question with only two possible responses, often 'yes' or 'no'.

A type of closed-ended question that offers multiple choices for the respondent to select from.

A closed-ended question that uses a scale with numbered or labeled points to measure opinions or attitudes.

A type of question that allows respondents to provide their own answers in their own words.

The data collected from a survey, representing different answers obtained for each question or variable.

The individual who completes a survey.

A systematic method for collecting data from a sample of individuals to gather information about a specific topic.

A symbol used in Sphinx Campus to identify the nature of a variable, providing information about its data type and how it can be analyzed.

A data type where responses are limited to pre-defined options, like 'yes' or 'no'.

A data type where respondents can select multiple options within a set of choices.

A data type that measures opinions or attitudes using a numerical scale with numbered or labeled points.

A data type that allows respondents to provide free-form, unconstrained answers in their own words.

A numeric variable that is a result of counting and can only be expressed as whole numbers.

A numeric variable that is a result of measuring and can take any value within a range, including decimals.

A type of question that asks respondents to rate their agreement or disagreement with a statement on a scale, typically from strongly agree to strongly disagree.

A variable that is classified into categories or groups. For example, gender (male, female) or colors (red, blue, green).

Numerical variables can either be discrete or continuous.

A Likert Scale Question is a type of categorical variable because it categorizes responses based on levels of agreement or disagreement.

A variable that represents numerical data. For example, age, height, or income.

Categorical variables are those that are classified into categories or groups.

Numeric variables can be transformed into categorical variables by creating groups or categories based on their values.

Numerical variables allow you to perform more complex statistical analyses, providing richer insights and more robust interpretations of data.

When possible, ask questions that generate numeric variables. If necessary, transform them into categorical variables.

Ensuring the data collected is accurate, complete, and without any manipulation.

The process of reviewing questionnaires to identify missing or incomplete information.

Dealing with missing data by substituting it with a neutral value like the average or most common value.

Removing observations with missing data entirely. Can lead to data loss if used too often.

Analyzing data by considering only complete observations for each individual analysis. Reduces bias introduced by missing data.

The process of transforming raw data into meaningful variables for analysis. Includes tasks like creating new variables or combining existing ones.

Defining the best statistical methods to use for analyzing the collected data. Involves choosing appropriate tests based on the research question and data type.

This involves identifying and removing errors or inconsistencies in the collected data, ensuring data quality and accuracy.

The 'Data' module in Sphinx Campus offers a range of functionalities for working with your collected data. You can analyze, filter, and check the quality of your data, including addressing non-responses.

Within the data module, you can apply filters to analyze your data based on specific criteria. This allows you to explore subsets of your data, gaining insights into specific groups of respondents.

Sphinx Campus provides tools to evaluate the quality of your survey sample. This helps you determine whether the data collected represents the intended population well.

Sphinx Campus accounts for situations where some participants do not respond to certain questions. It allows you to manage how you handle these non-responses, ensuring your analysis remains robust.

To work with the different functions of the 'Data' module, you need to open a survey. These surveys can be stored in your list of available surveys.

When opening a survey in the 'Data' module, you are presented with a spreadsheet showing all responses. This provides a comprehensive view of the collected data, including all answers to all questions.

The 'Data' module displays key information about the survey. You can see the name of the survey, the total number of responses, the nature of the sample, and whether the data can be altered.