# The graph shows the number of handbags that Mandy made in one day. What are the variables? Describe how the variables are related at various points on the graph

## To identify the variables and describe their relationship on the graph, we need to analyze the given information. Unfortunately, as an AI text-based bot, I cannot visualize or analyze graphs directly. However, I can explain to you how to interpret the variables and their relationship based on a typical graph scenario.

In a graph showing the number of handbags Mandy made in one day, there are typically two main variables. The independent variable, also known as the x-axis variable, usually represents time. In this case, it would represent the time points throughout the day. The dependent variable, also known as the y-axis variable, represents the number of handbags made by Mandy.

The relationship between the variables is observed by examining the pattern of the graph. Here are a few different scenarios that may explain the relationship at various points on the graph:

1. Increasing relationship: If the line in the graph is sloping upwards from left to right, it suggests a positive relationship between time and the number of handbags made. In other words, as time progresses, the number of handbags made by Mandy also increases.

2. Decreasing relationship: If the line in the graph is sloping downwards from left to right, it signifies a negative relationship. This means that as time progresses, the number of handbags made by Mandy decreases.

3. Constant relationship: If the line in the graph is horizontal, it indicates a constant relationship. This means that the number of handbags made by Mandy remains the same regardless of the time point during the day.

4. Fluctuating relationship: If the line in the graph is irregular, with no clear pattern of increase or decrease, it implies an inconsistent relationship between time and the number of handbags made. It could signify fluctuations in Mandy's productivity throughout the day.

Remember, this explanation is based on general assumptions about graph interpretation and may vary depending on the specifics of the given graph.