By the end of this submodule, participants will be able to:
- Understand the Significance of Trend Analysis:
Articulate the importance of trend analysis and forecasting in business decision-making and strategic planning.
- Identify Types of Trends:
Recognize different types of trends (short-term, long-term, and emerging) and their implications for businesses and industries.
- Apply Forecasting Techniques:
Utilize various quantitative and qualitative techniques for analyzing trends and making accurate forecasts.
- Evaluate Forecasting Methods:
Assess the reliability and validity of different forecasting methods, understanding their strengths and limitations in various contexts.
By the end of this submodule, participants will be able to:
- Understand the Significance of Trend Analysis:
Articulate the importance of trend analysis and forecasting in business decision-making and strategic planning.
- Identify Types of Trends:
Recognize different types of trends (short-term, long-term, and emerging) and their implications for businesses and industries.
- Apply Forecasting Techniques:
Utilize various quantitative and qualitative techniques for analyzing trends and making accurate forecasts.
- Evaluate Forecasting Methods:
Assess the reliability and validity of different forecasting methods, understanding their strengths and limitations in various contexts.
Trend analysis is the process of examining historical data to identify patterns or trends that can inform future predictions. It is essential for businesses to understand market dynamics, consumer behavior, and industry shifts in order to make informed decisions.
Key aspects of trend analysis include:
- Identifying Types of Trends:
- Short-term Trends: Fluctuations that occur over a brief period, often influenced by seasonal changes or specific events.
- Long-term Trends: Sustained movements that indicate a general direction over an extended period, such as demographic shifts or technological advancements.
- Emerging Trends: New patterns that are just beginning to develop and may significantly impact the market in the future.
- Importance of Trend Analysis:
- Provides insights into market conditions and consumer preferences.
- Helps identify growth opportunities and potential threats.
- Enables businesses to make data-driven decisions and adapt to changing market conditions.
Trend analysis is the process of examining historical data to identify patterns or trends that can inform future predictions. It is essential for businesses to understand market dynamics, consumer behavior, and industry shifts in order to make informed decisions.
Key aspects of trend analysis include:
- Identifying Types of Trends:
- Short-term Trends: Fluctuations that occur over a brief period, often influenced by seasonal changes or specific events.
- Long-term Trends: Sustained movements that indicate a general direction over an extended period, such as demographic shifts or technological advancements.
- Emerging Trends: New patterns that are just beginning to develop and may significantly impact the market in the future.
- Importance of Trend Analysis:
- Provides insights into market conditions and consumer preferences.
- Helps identify growth opportunities and potential threats.
- Enables businesses to make data-driven decisions and adapt to changing market conditions.
There are various techniques used for trend analysis and forecasting, which can be broadly categorized into quantitative and qualitative methods.
There are various techniques used for trend analysis and forecasting, which can be broadly categorized into quantitative and qualitative methods.
1. Time Series Analysis:
Involves statistical techniques to analyze data points collected or recorded at specific time intervals. Common methods include moving averages, exponential smoothing, and ARIMA models[1][2].
2. Regression Analysis:
A statistical method used to determine the relationship between variables and predict future values based on historical data[1][2].
3. Econometric Modeling:
Uses mathematical and statistical models to analyze economic factors and their relationships. This technique helps identify the underlying drivers of trends and make forecasts based on economic indicators[1][2].
1. Time Series Analysis:
Involves statistical techniques to analyze data points collected or recorded at specific time intervals. Common methods include moving averages, exponential smoothing, and ARIMA models[1][2].
2. Regression Analysis:
A statistical method used to determine the relationship between variables and predict future values based on historical data[1][2].
3. Econometric Modeling:
Uses mathematical and statistical models to analyze economic factors and their relationships. This technique helps identify the underlying drivers of trends and make forecasts based on economic indicators[1][2].
1. Expert Opinion:
Gathering insights from industry experts or stakeholders to identify potential trends and future developments[1][2].
2. Focus Groups:
Conducting discussions with selected individuals to gather qualitative data on consumer preferences and emerging trends[1][2].
3. Market Research:
Collecting data directly from consumers through surveys, questionnaires, and social media analysis to understand their preferences and behaviors[1][2].
1. Expert Opinion:
Gathering insights from industry experts or stakeholders to identify potential trends and future developments[1][2].
2. Focus Groups:
Conducting discussions with selected individuals to gather qualitative data on consumer preferences and emerging trends[1][2].
3. Market Research:
Collecting data directly from consumers through surveys, questionnaires, and social media analysis to understand their preferences and behaviors[1][2].
Developing multiple scenarios based on different assumptions about the future. This technique helps organizations prepare for various possibilities and uncertainties[1][2].
Developing multiple scenarios based on different assumptions about the future. This technique helps organizations prepare for various possibilities and uncertainties[1][2].
Forecasting is the process of making predictions about future events based on historical data and analysis. It helps organizations plan for the future and make informed decisions.
Key benefits of forecasting include:
- Improved resource allocation and budgeting.
- Enhanced strategic planning and risk management.
- Better understanding of market opportunities and threats.
- Ability to anticipate and adapt to changes in the market[1][2].
Forecasting is the process of making predictions about future events based on historical data and analysis. It helps organizations plan for the future and make informed decisions.
Key benefits of forecasting include:
- Improved resource allocation and budgeting.
- Enhanced strategic planning and risk management.
- Better understanding of market opportunities and threats.
- Ability to anticipate and adapt to changes in the market[1][2].
Trend analysis and forecasting are essential tools for businesses to navigate the complexities of the market and make informed decisions. By understanding different types of trends and applying various quantitative and qualitative techniques, organizations can enhance their ability to predict future events and position themselves for success.
Trend analysis and forecasting are essential tools for businesses to navigate the complexities of the market and make informed decisions. By understanding different types of trends and applying various quantitative and qualitative techniques, organizations can enhance their ability to predict future events and position themselves for success.
[1] https://www.notion.so/blog/business-forecasting
[2] https://www.investopedia.com/terms/f/forecasting.asp
[3] https://hbr.org/1971/07/how-to-choose-the-right-forecasting-technique
[4] https://explodingtopics.com/blog/trend-forecasting
[5] https://www.meltwater.com/en/blog/trend-forecasting-prediction
[1] https://www.notion.so/blog/business-forecasting
[2] https://www.investopedia.com/terms/f/forecasting.asp
[3] https://hbr.org/1971/07/how-to-choose-the-right-forecasting-technique
[4] https://explodingtopics.com/blog/trend-forecasting
[5] https://www.meltwater.com/en/blog/trend-forecasting-prediction
1. Quantitative Methods
A. Time Series Analysis
Time series analysis involves statistical techniques to analyze data points collected or recorded at specific time intervals. It is particularly useful for identifying trends, seasonal patterns, and cyclical movements in historical data.
- Key Techniques:
- Moving Averages: This method smooths out short-term fluctuations and highlights longer-term trends by averaging data points over a specified period (e.g., 3-month, 12-month).
- Exponential Smoothing: A forecasting technique that applies decreasing weights to older data points, giving more importance to recent observations.
- ARIMA Models (AutoRegressive Integrated Moving Average): A sophisticated statistical model that combines autoregression, differencing, and moving averages to forecast future values based on past data.
B. Regression Analysis
Regression analysis is a statistical method used to determine the relationship between variables and predict future values based on historical data. It can help identify how changes in one variable (independent variable) affect another variable (dependent variable).
- Types of Regression:
- Simple Linear Regression: Analyzes the relationship between two variables by fitting a straight line to the data points.
- Multiple Regression: Examines the relationship between one dependent variable and multiple independent variables, allowing for a more comprehensive analysis.
C. Econometric Modeling
Econometric modeling uses mathematical and statistical models to analyze economic factors and their relationships. This technique helps identify the underlying drivers of trends and make forecasts based on economic indicators.
- Application: Econometric models can be used to analyze the impact of factors such as interest rates, inflation, and consumer spending on economic growth and market trends.
1. Quantitative Methods
A. Time Series Analysis
Time series analysis involves statistical techniques to analyze data points collected or recorded at specific time intervals. It is particularly useful for identifying trends, seasonal patterns, and cyclical movements in historical data.
- Key Techniques:
- Moving Averages: This method smooths out short-term fluctuations and highlights longer-term trends by averaging data points over a specified period (e.g., 3-month, 12-month).
- Exponential Smoothing: A forecasting technique that applies decreasing weights to older data points, giving more importance to recent observations.
- ARIMA Models (AutoRegressive Integrated Moving Average): A sophisticated statistical model that combines autoregression, differencing, and moving averages to forecast future values based on past data.
B. Regression Analysis
Regression analysis is a statistical method used to determine the relationship between variables and predict future values based on historical data. It can help identify how changes in one variable (independent variable) affect another variable (dependent variable).
- Types of Regression:
- Simple Linear Regression: Analyzes the relationship between two variables by fitting a straight line to the data points.
- Multiple Regression: Examines the relationship between one dependent variable and multiple independent variables, allowing for a more comprehensive analysis.
C. Econometric Modeling
Econometric modeling uses mathematical and statistical models to analyze economic factors and their relationships. This technique helps identify the underlying drivers of trends and make forecasts based on economic indicators.
- Application: Econometric models can be used to analyze the impact of factors such as interest rates, inflation, and consumer spending on economic growth and market trends.
2. Qualitative Methods
A. Expert Opinion
Gathering insights from industry experts or stakeholders can provide valuable qualitative data on potential trends and future developments. This method leverages the knowledge and experience of individuals who are well-versed in the industry.
- Application: Conduct interviews or surveys with experts to gather their perspectives on emerging trends and potential market shifts.
B. Focus Groups
Focus groups involve conducting discussions with selected individuals to gather qualitative data on consumer preferences, behaviors, and attitudes. This method allows for in-depth exploration of ideas and opinions.
- Application: Organize focus group sessions to discuss specific products, services, or market trends, capturing participants' insights and feedback.
C. Market Research
Market research involves collecting data directly from consumers through surveys, questionnaires, and social media analysis. This technique helps organizations understand consumer preferences and behaviors.
- Application: Use online surveys to gather data on consumer opinions, preferences, and buying behaviors, which can inform trend analysis and forecasting efforts.
3. Scenario Planning
Scenario planning is a strategic technique that involves developing multiple scenarios based on different assumptions about the future. This approach helps organizations prepare for various possibilities and uncertainties.
- Key Components:
- Identify Key Drivers: Determine the factors that could influence future trends (e.g., technological advancements, regulatory changes, economic conditions).
- Develop Scenarios: Create a range of plausible scenarios based on different combinations of key drivers and assumptions.
- Analyze Implications: Assess the potential impact of each scenario on the organization, identifying opportunities and threats.
- Application: Use scenario planning to inform strategic decision-making, helping organizations navigate uncertainties and adapt to changing market conditions.
2. Qualitative Methods
A. Expert Opinion
Gathering insights from industry experts or stakeholders can provide valuable qualitative data on potential trends and future developments. This method leverages the knowledge and experience of individuals who are well-versed in the industry.
- Application: Conduct interviews or surveys with experts to gather their perspectives on emerging trends and potential market shifts.
B. Focus Groups
Focus groups involve conducting discussions with selected individuals to gather qualitative data on consumer preferences, behaviors, and attitudes. This method allows for in-depth exploration of ideas and opinions.
- Application: Organize focus group sessions to discuss specific products, services, or market trends, capturing participants' insights and feedback.
C. Market Research
Market research involves collecting data directly from consumers through surveys, questionnaires, and social media analysis. This technique helps organizations understand consumer preferences and behaviors.
- Application: Use online surveys to gather data on consumer opinions, preferences, and buying behaviors, which can inform trend analysis and forecasting efforts.
3. Scenario Planning
Scenario planning is a strategic technique that involves developing multiple scenarios based on different assumptions about the future. This approach helps organizations prepare for various possibilities and uncertainties.
- Key Components:
- Identify Key Drivers: Determine the factors that could influence future trends (e.g., technological advancements, regulatory changes, economic conditions).
- Develop Scenarios: Create a range of plausible scenarios based on different combinations of key drivers and assumptions.
- Analyze Implications: Assess the potential impact of each scenario on the organization, identifying opportunities and threats.
- Application: Use scenario planning to inform strategic decision-making, helping organizations navigate uncertainties and adapt to changing market conditions.
These techniques for trend analysis and forecasting provide organizations with the tools needed to understand market dynamics and make informed decisions. By combining quantitative and qualitative methods, as well as employing scenario planning, businesses can enhance their ability to predict future trends and position themselves for success.
These techniques for trend analysis and forecasting provide organizations with the tools needed to understand market dynamics and make informed decisions. By combining quantitative and qualitative methods, as well as employing scenario planning, businesses can enhance their ability to predict future trends and position themselves for success.
1. "The Signal and the Noise: Why So Many Predictions Fail—but Some Don't" by Nate Silver
- Overview: This book explores the art of prediction and the importance of distinguishing between meaningful signals and irrelevant noise in data. It provides insights into various forecasting techniques and their applications.
2. "Competing on Analytics: The New Science of Winning" by Thomas H. Davenport and Jeanne G. Harris
- Overview: This book discusses how organizations can leverage data analytics for competitive advantage, including trend analysis and forecasting techniques. It offers case studies and practical examples.
3. "The Lean Six Sigma Pocket Toolbook" by Michael L. George, John Maxey, David Rowlands, and Malcom Upton
- Overview: While not exclusively focused on trend analysis, this book provides practical tools and techniques for data analysis and problem-solving, which can be applied in forecasting efforts.
1. "The Signal and the Noise: Why So Many Predictions Fail—but Some Don't" by Nate Silver
- Overview: This book explores the art of prediction and the importance of distinguishing between meaningful signals and irrelevant noise in data. It provides insights into various forecasting techniques and their applications.
2. "Competing on Analytics: The New Science of Winning" by Thomas H. Davenport and Jeanne G. Harris
- Overview: This book discusses how organizations can leverage data analytics for competitive advantage, including trend analysis and forecasting techniques. It offers case studies and practical examples.
3. "The Lean Six Sigma Pocket Toolbook" by Michael L. George, John Maxey, David Rowlands, and Malcom Upton
- Overview: While not exclusively focused on trend analysis, this book provides practical tools and techniques for data analysis and problem-solving, which can be applied in forecasting efforts.
1. "The Future of Everything"
- Overview: This podcast explores emerging trends and technologies across various industries, featuring insights from experts and innovators. It provides valuable perspectives on potential future developments.
2. "Trend Following"
- Overview: A podcast that discusses market trends, investment strategies, and forecasting techniques with industry professionals. It offers practical advice and case studies.
3. "Freakonomics Radio"
- Overview: This podcast explores the hidden side of everything, often using data and economic principles to analyze trends and make predictions. It provides a unique perspective on various topics.
1. "The Future of Everything"
- Overview: This podcast explores emerging trends and technologies across various industries, featuring insights from experts and innovators. It provides valuable perspectives on potential future developments.
2. "Trend Following"
- Overview: A podcast that discusses market trends, investment strategies, and forecasting techniques with industry professionals. It offers practical advice and case studies.
3. "Freakonomics Radio"
- Overview: This podcast explores the hidden side of everything, often using data and economic principles to analyze trends and make predictions. It provides a unique perspective on various topics.
1. "How to Use Trend Analysis to Predict the Future" - Harvard Business Review
- Overview: This article outlines a step-by-step approach to using trend analysis for forecasting, emphasizing the importance of identifying patterns and making data-driven decisions.
- How to Access: Search for the title on the Harvard Business Review website.
2. "The Power of Scenario Planning in a Changing World" - McKinsey & Company
- Overview: This article discusses the benefits of scenario planning and how organizations can use it to navigate uncertainty and make informed decisions.
- How to Access: Search for the title on the McKinsey & Company website.
1. "How to Use Trend Analysis to Predict the Future" - Harvard Business Review
- Overview: This article outlines a step-by-step approach to using trend analysis for forecasting, emphasizing the importance of identifying patterns and making data-driven decisions.
- How to Access: Search for the title on the Harvard Business Review website.
2. "The Power of Scenario Planning in a Changing World" - McKinsey & Company
- Overview: This article discusses the benefits of scenario planning and how organizations can use it to navigate uncertainty and make informed decisions.
- How to Access: Search for the title on the McKinsey & Company website.
1. Coursera: "Business Analytics"
- Overview: This course covers data analysis techniques, including trend analysis and forecasting methods. It provides hands-on experience with statistical software and case studies.
2. LinkedIn Learning: "Forecasting and Predictive Analytics"
- Overview: This course provides practical insights into forecasting techniques and their applications in business decision-making. It covers both quantitative and qualitative methods.
3. Udemy: "Trend Analysis and Forecasting for Business"
- Overview: This course offers a comprehensive overview of trend analysis and forecasting, including time series analysis, regression, and scenario planning. It includes case studies and practical exercises.
1. Coursera: "Business Analytics"
- Overview: This course covers data analysis techniques, including trend analysis and forecasting methods. It provides hands-on experience with statistical software and case studies.
2. LinkedIn Learning: "Forecasting and Predictive Analytics"
- Overview: This course provides practical insights into forecasting techniques and their applications in business decision-making. It covers both quantitative and qualitative methods.
3. Udemy: "Trend Analysis and Forecasting for Business"
- Overview: This course offers a comprehensive overview of trend analysis and forecasting, including time series analysis, regression, and scenario planning. It includes case studies and practical exercises.
Activity 1: Trend Identification and Analysis Workshop
Objective:
To identify and analyze current trends relevant to participants' industries or interests.
Activity Structure:
1. Group Formation (5 minutes):
Divide participants into small groups based on similar industries or interests.
2. Trend Research (20 minutes):
Each group conducts research to identify at least two current trends affecting their industry. They can use online resources, news articles, and industry reports to gather information.
3. Trend Analysis (15 minutes):
Groups analyze the identified trends by answering the following questions:
- What are the key drivers of these trends?
- How are these trends impacting consumer behavior?
- What opportunities or threats do these trends present for businesses?
4. Presentation (15 minutes):
Each group presents their findings to the larger group, highlighting the implications of the identified trends for their industry. Encourage discussion and questions from other participants.
Activity 1: Trend Identification and Analysis Workshop
Objective:
To identify and analyze current trends relevant to participants' industries or interests.
Activity Structure:
1. Group Formation (5 minutes):
Divide participants into small groups based on similar industries or interests.
2. Trend Research (20 minutes):
Each group conducts research to identify at least two current trends affecting their industry. They can use online resources, news articles, and industry reports to gather information.
3. Trend Analysis (15 minutes):
Groups analyze the identified trends by answering the following questions:
- What are the key drivers of these trends?
- How are these trends impacting consumer behavior?
- What opportunities or threats do these trends present for businesses?
4. Presentation (15 minutes):
Each group presents their findings to the larger group, highlighting the implications of the identified trends for their industry. Encourage discussion and questions from other participants.
Activity 2: Forecasting Scenario Planning Exercise
Objective:
To develop multiple scenarios based on different assumptions about future trends.
Activity Structure:
1. Define the Focus Area (5 minutes):
Participants select a specific trend or market condition to analyze. This could be a trend identified in the previous activity or a new one.
2. Scenario Development (20 minutes):
In groups, participants develop three different scenarios based on varying assumptions about the trend:
- Best-case scenario: What happens if the trend develops positively?
- Worst-case scenario: What happens if the trend takes a negative turn?
- Most likely scenario: What is the most probable outcome based on current data?
3. Scenario Analysis (15 minutes):
Each group discusses the implications of their scenarios, considering factors such as market dynamics, consumer behavior, and competitive landscape.
4. Presentation and Discussion (15 minutes):
Each group presents their scenarios and discusses the potential implications for their businesses. Encourage feedback and suggestions from other participants.
Activity 2: Forecasting Scenario Planning Exercise
Objective:
To develop multiple scenarios based on different assumptions about future trends.
Activity Structure:
1. Define the Focus Area (5 minutes):
Participants select a specific trend or market condition to analyze. This could be a trend identified in the previous activity or a new one.
2. Scenario Development (20 minutes):
In groups, participants develop three different scenarios based on varying assumptions about the trend:
- Best-case scenario: What happens if the trend develops positively?
- Worst-case scenario: What happens if the trend takes a negative turn?
- Most likely scenario: What is the most probable outcome based on current data?
3. Scenario Analysis (15 minutes):
Each group discusses the implications of their scenarios, considering factors such as market dynamics, consumer behavior, and competitive landscape.
4. Presentation and Discussion (15 minutes):
Each group presents their scenarios and discusses the potential implications for their businesses. Encourage feedback and suggestions from other participants.
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To evaluate past performance | |
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To identify patterns for future predictions | |
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To allocate resources | |
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To finalize business strategies |
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True | |
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False |
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Focus groups | |
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Expert opinion | |
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Time series analysis | |
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Surveys |
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True | |
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False |
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Short-term | |
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Long-term | |
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Random | |
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Emerging |
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True | |
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False |
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It provides quantitative data | |
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It offers insights based on experience and industry knowledge | |
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It eliminates the need for data analysis | |
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It guarantees accurate predictions |
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True | |
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False |
Key Takeaways
- Importance of Trend Analysis:
Understanding trends is crucial for making informed business decisions and anticipating market changes. It helps organizations identify opportunities and mitigate risks.
- Types of Trends:
- Short-term Trends: Fluctuations over brief periods, often seasonal.
- Long-term Trends: Sustained movements indicating general direction.
- Emerging Trends: New patterns that may significantly impact the market.
- Forecasting Techniques:
- Quantitative Methods: Time series analysis, regression analysis, and econometric modeling.
- Qualitative Methods: Expert opinion, focus groups, and market research.
- Scenario Planning: Developing multiple plausible futures based on different assumptions.
Key Takeaways
- Importance of Trend Analysis:
Understanding trends is crucial for making informed business decisions and anticipating market changes. It helps organizations identify opportunities and mitigate risks.
- Types of Trends:
- Short-term Trends: Fluctuations over brief periods, often seasonal.
- Long-term Trends: Sustained movements indicating general direction.
- Emerging Trends: New patterns that may significantly impact the market.
- Forecasting Techniques:
- Quantitative Methods: Time series analysis, regression analysis, and econometric modeling.
- Qualitative Methods: Expert opinion, focus groups, and market research.
- Scenario Planning: Developing multiple plausible futures based on different assumptions.
Call to Action
- Apply trend analysis and forecasting techniques in your strategic planning processes. Stay proactive in monitoring market dynamics to ensure your organization remains competitive and adaptable.
Call to Action
- Apply trend analysis and forecasting techniques in your strategic planning processes. Stay proactive in monitoring market dynamics to ensure your organization remains competitive and adaptable.
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Section completed | ![]() |
Exercise | Result | Your answer | Correct answer |