Data Analysis & Statistics — A Practical Course for Beginners

this lesson introduces the course and its objectives.

learn the importance of data planning and what will be covered in this module.

discover the initial steps for effective data planning.

explore the philosophical question about the origins of data.

understand the two main types of data used in analysis.

learn how to select the appropriate data analysis method.

find out effective strategies for locating data.

explore how to find previously collected data from other sources.

learn how to commission a research company to collect data.

understand the process of collecting data on your own.

discover the significance of data exploration and what it entails.

learn how to explore data through direct observation.

understand how to gather data through interviews.

explore methods for analyzing data through reading relevant materials.

learn how to analyze data by reviewing scientific articles.

discover additional sources for data exploration.

learn how to eliminate duplicates and properly name your variables.

create a model to facilitate data analysis.

understand the importance of data collection and what it involves.

learn how to effectively choose respondents for your study.

discover how to determine the appropriate sample size for your research.

get general guidelines on how to create an effective survey.

learn how to select different types of questions for your survey.

understand how to choose types of variable measurement for your survey.

learn about the various measurement scales to use in surveys.

learn how to create the actual survey for your data collection.

discover how to test your survey to ensure its effectiveness.

explore various data collection methods to gather information.

understand how to use Google Forms for online data collection.

learn strategies to promote your survey and increase responses.

get an overview of data preparation and its importance.

examine your dataset to understand its structure and content.

learn how to remove unwanted data from your dataset.

identify and mark missing data within your dataset.

discover five key things to watch out for in data formatting.

learn how to eliminate white spaces in your dataset.

correct typos in your data to improve accuracy.

ensure consistent capitalization throughout your dataset.

learn how to change incompatible data units for consistency.

assign the correct data types to improve data integrity.

transform your data to meet specific analysis requirements.

gain an overview of data analysis and its significance.

understand descriptive statistics and their role in data analysis.

analyze data distribution to check for normality.

apply descriptive statistics practically to your dataset.

learn about inferential statistics and their application in analysis.

choose the right statistical software based on your analysis method.

download statistical software to begin your analysis.

tour the interface of the statistical software you downloaded.

create a project and import your data into the software.

Learn how to create data groups for analysis.

Discover how to build a model using statistical software.

Explore various methods and procedures for data analysis.

Get an overview of data monetization and its significance.

Learn how to visualize data to effectively tell your story.

Explore various types of charts used in data visualization.

Apply data visualization techniques to create impactful presentations.

Utilize your results for product development purposes.

Leverage your results to enhance sales strategies.

Use your results to inform marketing strategies.

Wrap up the course with a conclusion.