Week 12-13 Flashcards
process of inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making.
Data analysis
Different types of Data in Research
• Quantitative Data
• Qualitative Data
• Mixed Methods Data
Methods of Data Analysis
• Descriptive Analysis
• Inferential Analysis
• Exploratory Analysis
Information expressed in numbers and measurable quantities. Examples include survey responses and experimental data.
Quantitative Data
Descriptive data that cannot be easily measured or expressed numerically. It involves observations, interviews, and focus groups.
Qualitative Data
A combination of quantitative and qualitative data to gain a comprehensive understanding of
the research topic.
Mixed Methods Data
Summarizing and describing the main characteristics of data, such as mean, median, and standard deviation.
Descriptive Analysis
Using statistical techniques to make predictions and generalizations about a larger population based on a sample of data.
Inferential Analysis
Identifying patterns, relationships, and trends to generate new hypotheses and insights.
Exploratory Analysis
Tools like R, Python, and Excel
provide powerful capabilities for
processing, analyzing, and
visualizing data.
Data Analysis Software
Graphical representation of data
using charts, maps, and graphs
to help gain insights and communicate findings effectively.
Data Visualization
Data Visualization Formats
• Bar Charts
• Pie/donut Chart
• Line Chart
• Bubble Chart
• Map
• Table
Compare numerical data and demonstrate growth
Bar Charts
Show how individual parts make up a whole
Pie/donut chart
Demonstrate change and progress
Line chart
Visualize relationships among numerical variables
Bubble chart
Represent any data that has to do with geolocation
Map
Compare data, show prices for services, create reports, etc
Table
A form of visually displaying data
through various methods like
graphs, diagrams, charts, and plots.
Graphical Representation
Ensuring the accuracy, completeness, and reliability of data by addressing missing values, outliers, and inconsistencies.
Data Quality
Protecting sensitive information and
adhering to ethical guidelines in handling and sharing data.
Data Privacy
a powerful tool that helps researchers explore and communicate their findings more
effectively. Through charts, graphs, and infographics, patterns and trends in the data become more accessible and understandable to a wider audience. It enhances the impact of research and facilitates decision-making processes.
Data visualization
