Using the years as the base of the graph and a scale of 2 cm to represent 10,000 tonnes of palm oil on the vertical axis, construct a grouped bar graph to represent the data

I have the data from Table Y (from your previous message) and the questions from the current image. Here are the answers to Question 2: a) To construct a grouped bar graph for the palm oil production data: Step 1: Set up the axes. • Draw a horizontal axis (x-axis) and label it "Years". Mark two distinct sections for the years 2020 and 2021. • Draw a vertical axis (y-axis) and label it "Palm Oil Production (tonnes)". Step 2: Apply the scale to the vertical axis. • Using the given scale of 2 cm to represent 10,000 tonnes, mark intervals on the vertical axis. For example, 2 cm for 10,000 tonnes, 4 cm for 20,000 tonnes, and so on, extending up to at least 150,000 tonnes (the highest production value). Step 3: Draw the grouped bars. • For each year (2020 and 2021), draw three adjacent bars representing the production for Region X, Region Y, and Region Z. • The heights of the bars should correspond to the following values based on the vertical scale: • For 2020: Region X (120,000 tonnes), Region Y (100,000 tonnes), Region Z (80,000 tonnes). • For 2021: Region X (150,000 tonnes), Region Y (110,000 tonnes), Region Z (90,000 tonnes). • Use different shading or colors for each region (X, Y, Z) to distinguish them clearly. Step 4: Add a legend and title. • Include a legend to identify which shading/color corresponds to which region. • Give the graph a clear and descriptive title, such as "Palm Oil Production by Region (2020-2021)". b) Three advantages of using a grouped bar graph (a cartographic method) to represent the data are: • Easy Comparison: It allows for straightforward visual comparison of palm oil production between different regions within the same year, and also for comparing a single region's production across the two years. • Clarity and Simplicity: The data is presented in a clear, simple, and easily understandable format, making it accessible even to those without a technical background. • Highlighting Trends: It effectively highlights trends, patterns, and significant differences in production values over time and across different regions. Send me the next one 📸