Research Skills & Analysis - Summary Lectures 1-3

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Questions and Answers

Match the following types of data with their definitions:

Primary data = Data already available from other sources Secondary data = Data collected directly from the subjects being studied Qualitative data = Data that can be categorized based on traits and characteristics Quantitative data = Data that can be measured numerically

Match the following data collection methods with their descriptions:

Surveys = A method of collecting data by asking questions Experiments = A method to test hypotheses under controlled conditions Observation = Collecting data by watching subjects in their natural environment Interviews = A method of data collection through face-to-face conversations

Match the following data types with their characteristics:

Primary data = Up-to-date information collected for a specific purpose Secondary data = Often less accurate due to being gathered by others Quantitative data = Represents observational data in numerical form Qualitative data = Descriptive and subjective information

Match the following research types with their focus:

Descriptive research = Focuses on describing characteristics of a population Exploratory research = Seeks to explore and understand an issue Causal research = Aims to determine cause-and-effect relationships Comparative research = Investigates differences between groups or variables Signup and view all the answers

Match the following data reliability concepts with their meanings:

Validity = The degree to which a study accurately reflects the concept it aims to measure Reliability = The consistency of a measure across time and various contexts Bias = Systemic errors that can influence the results of data collection Generalizability = The extent to which findings can be applied to larger populations Signup and view all the answers

Match the following data processing terms with their descriptions:

Data Cleansing = The process of removing inaccuracies from data Data Integration = Combining data from different sources into a unified view Data Transformation = Converting data from one format to another Data Storage = The method of saving data for future use Signup and view all the answers

Match the following types of data with their characteristics:

Structured Data = Data that is organized and easily searchable Unstructured Data = Data that does not have a predefined data model Semi-structured Data = Data that does not conform to a rigid structure but has some organizational properties Metadata = Data that provides information about other data Signup and view all the answers

Match the following data analysis techniques with their purposes:

Descriptive Analysis = Summarizes past data to understand trends Predictive Analysis = Forecasts future outcomes based on historical data Prescriptive Analysis = Recommends actions based on data analysis Diagnostic Analysis = Identifies reasons for past outcomes or trends Signup and view all the answers

Match the following roles in data processing with their responsibilities:

Data Scientist = Analyzes complex data to derive insights Data Engineer = Builds and maintains data architecture and pipelines Database Administrator = Manages and organizes data stored in databases Data Analyst = Interprets data and provides actionable insights Signup and view all the answers

Match the following data visualization tools with their primary features:

Tableau = Interactive data visualization and dashboards Microsoft Power BI = Business analytics and reporting Google Data Studio = Free data visualization tools with web integration D3.js = JavaScript library for producing dynamic, interactive data visualizations Signup and view all the answers

Study Notes

Research Skills & Analysis - Summary Lectures (1-3)

Data are individual facts, observations, statistics, characters, symbols, images, numbers, and more. Out of context, they have no meaning and are hard to understand. Raw data.
Research data are classified as quantitative or qualitative.
Quantitative data can be counted or expressed numerically.
Qualitative data are descriptive and have no numerical values.

Types of Data

Primary data is collected by a researcher for the specific problem at hand, directly from the subjects.
Secondary data is already available, collected from other sources.

Data Collection Methods

Data collection is essential; study conclusions are based on the data.
Methods include: observation, questionnaires, interviews, surveys, and experimental devices.
Observation is a research technique involving direct observation of phenomena in natural settings.
- Participant observation: researcher becomes part of the group being studied (observer loses objectivity)
- Non-participant observation: researcher observes from a distance without participating.
- Systematic controlled observation: researcher pre-determines variables, location, time, participants, and tools.
A questionnaire is a series of written questions presented to subjects.
- Structured (closed) questionnaires have predetermined answers.
- Unstructured (open) questionnaires use open-ended questions.
Interview is more than an oral exchange. It involves focused conversation with a purpose.
- Non-directive interview: flexible and unstructured.
- Directive interview: has a predefined set of questions.
- Repeated interview: tracks changes over time.
- Focused interview : explores specific views.
- Depth interview: intensive interviews with a small group.
Surveys are research methods where subjects respond to statements or questions (questionnaire or interview). Often involving sampling of a population to represent the whole.
- Random sampling ensures the sample represents the entire population.

Information

Information is processed data, presented meaningfully.
- Stages include: collection, preparation, input, processing, output, and storage.

Data Processing

Raw data is not usable. Processed data produces useful information.
Process involves: data collection, data preparation (validation), sorting (descriptive or numerical), input (machine readable, keyboard, scanner), processing/analysis.
Data Analysis Using a Computer: Knowledge of the statistical software program is key. Output/interpretation makes data usable to non-specialists. Storage saves data and metadata for future use.
Different data processing types exist (Batch, Real-time, Online, Time-sharing).

Statistical Analysis

Statistical analysis is a scientific tool for collecting and analyzing large amounts of data.
Descriptive analysis includes measures of central tendency (mean, median, mode) and variability (range, standard deviation, variance, interquartile range).
Inferential analysis uses analytical tools for drawing conclusions about a population based on random samples. It aims to generalize research for a population.
Associative/relative analysis explores meaningful interrelationships between data.

Statistical software

Major softwares: SPSS, Microsoft Excel, Matlab, OriginPro, Minitab, GraphPad Prism.

Databases

A database is a collection of organized information for easy access, management, and updating.
Types include:
- Relational database: Collection of tables of data items. Tables have rows and columns (attributes/tuples).
- Document-oriented database: Stores information in documents (JSON like). Primarily non-relational.
- Graph database: Uses graph structures with nodes, edges, and properties to represent data.
- Hypertext database: Objects (text, pictures, etc) linked creatively. Primarily in HTML.
- Operational database: Designed for real-time data definition, modification, retrieval, and management. Tracks organizational activity.
- Distributed database: Portions stored on multiple computers in a network.
- Flat-file database: Stores data in a single table in plain text formats. Primarily for small amounts of data.
Rows (tuples) and columns (attributes) represent data. Primary and Foreign Keys are used for unique identification of fields.

Data & Information & Knowledge

Knowledge is a blend of information, experience, and insight for understanding. Information answers "w/w/w", but knowledge answers "why/how".
Different sources (Unscientific/Scientific/Divine) exist for acquiring knowledge.
Unscientific sources include: Empiricism (objective observation), Trial and Error, Tradition (local knowledge), Tenacity (belief based on repetition), Rationalism (logical reasoning), Authority (respected figures).
Scientific sources are based on empirical evidence and appropriate for understanding the natural world. Scientific Knowledge is durable, strong, and open to change.
Characteristics of scientific knowledge: Objectivity (seeing facts as they are), Verifiability/Measurability (evidence verifiable), Reliability (stability of results).

The Meaning of Research

Research is finding solutions to problems. It is an investigative process to discover new knowledge.
"Research" is the combination of "re" (again or anew) and "search" (explore).

Types of Research

Application: Pure research (for greater knowledge of fundamental phenomena) and applied research (applying pure research outcomes to real-world situations).
Objectives: Exploratory research (in a new area), descriptive research (describing characteristics), correlational research (relationship between two variables), explanatory research (explaining reasons for occurrences).
Enquiry Mode: Qualitative research (unstructured, words, impressions); quantitative research (structured, numerical).

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Description

This quiz covers the foundational concepts of research skills and data analysis as presented in the summary lectures. It explores the distinctions between quantitative and qualitative data, primary and secondary data, as well as various data collection methods. Help reinforce your understanding of these essential research methodologies.