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Introduction to analysis methods

1. Introduction to analysis methods

In this video we'll learn to apply analysis methods to optimize the decision-making process.

2. Analyze to thrive

Analysis is a vital part of decision-making. It provides insights into relevant data, uncovers patterns, identifies trends, evaluates alternatives, and their potential outcomes. In the decision-making process, analysis is directly involved in step 4: "Evaluate alternatives". This is a key step when all the data, the options and each potential output are evaluated before making a decision.

3. Types of analysis

There are two types of analysis: quantitative and qualitative. These approaches are not mutually exclusive; instead, they complement each other. Combining quantitative and qualitative methods provide a comprehensive approach to analysis!

4. Types of analysis

Quantitative analysis involves the use of numerical data and mathematical or statistical techniques to analyze events, trends or relationships.

5. Types of analysis

On the other hand, qualitative analysis involves the examination and interpretation of non-numerical data such as text, images, or observations to understand meanings, patterns, and relationships.

6. Quantitative analysis

Quantitative methods provide precise measurements and enable statistical analysis to improve the accuracy of interpretations and inferences. As examples, we have, Descriptive statistics applying math concepts such as average, medium, and mode to characterize the data.

7. Quantitative analysis

Inferential statistics uses numerical relationships, hypothesis and estimations to raise insights from sample data, expanding the analysis range, making inferences or predictions about a larger population.

8. Quantitative analysis

Probability distributions map probabilities to outcomes, quantifying likelihood and enabling forecasts. This analysis method provide useful mathematical tools to help us deal with uncertainties.

9. Qualitative analysis

Qualitative analysis involves gathering and interpreting non-numerical data to gain insights into human behavior, perceptions, and experiences. As an example of qualitative method, we have SWOT Analysis. This tool helps the identification of internal strengths and weaknesses as well as external opportunities and threats. This allow individuals and teams to assess their current situation and make informed decisions.

10. Qualitative analysis

Another example of qualitative analysis are Fishbone Diagrams. These visual tools are helpful when you need to identify the root causes of a specific problem. The issue or effect being investigated is at the head of the fish and potential causes branches out like bones. A visualization like this can help you organize and categorize the descriptive factors associated with your decision problem.

11. Analysis tools

Today there is a great variety of tools to increase efficiency, accuracy, and scalability in handling data and conducting investigations during an analysis. One example, are spreadsheets. These popular tools are very useful in the organization, visualization, and interpretation of data.

12. Analysis tools

Statistical programming languages such as Matlab, R and Python offer powerful capabilities for conducting complex data analysis, including statistical modeling, machine learning, and data visualization, enabling analysts to produce valuable insights from data.

13. Analysis tools

Lastly, Decision Support Systems like IBM Watson, Qlikview and PowerBI provide advanced analytics capabilities, interactive visualizations, and data-driven insights, empowering users to make informed decisions based on real-time data analysis.

14. Let's practice!

Enough talking, it`s time to practice!

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