plotted point

简明释义

标出点

英英释义

例句

1.To create a line graph, we connected the plotted points with straight lines.

为了创建折线图，我们用直线连接了绘制的点。

2.The scientist analyzed the plotted points to identify trends in the data.

科学家分析了绘制的点以识别数据中的趋势。

3.The plotted point at (3, 5) indicates a significant increase in sales.

坐标(3, 5)的绘制的点表示销售额显著增加。

4.Each plotted point on the scatter plot corresponds to a specific measurement.

散点图上的每个绘制的点对应于一个特定的测量值。

5.In the graph, each plotted point represents a different data entry.

在图表中，每个绘制的点代表一个不同的数据条目。

作文

In the world of mathematics and data visualization, the term plotted point refers to a specific location on a graph that represents a particular value or set of values. Understanding how to interpret these points is crucial for analyzing trends and making informed decisions based on data. For instance, when we create a scatter plot to display the relationship between two variables, each plotted point corresponds to the intersection of the values of those variables. This visual representation allows us to quickly discern patterns, correlations, and outliers within the dataset.Consider a scenario where a researcher is studying the impact of exercise on weight loss. By collecting data from a group of participants, they can create a scatter plot with 'hours of exercise per week' on the x-axis and 'weight lost in pounds' on the y-axis. Each participant's data will be represented by a plotted point, allowing the researcher to observe how different levels of exercise correlate with weight loss. If the points cluster in a linear fashion, it suggests a positive correlation; as exercise increases, weight loss also tends to increase.Moreover, the placement of each plotted point can reveal significant insights. For example, if most points lie along a straight line but a few are far removed from this line, these outliers may indicate exceptional cases or errors in data collection. Understanding these plotted points helps researchers refine their hypotheses and improve the accuracy of their conclusions.In addition to scatter plots, plotted points are also essential in other types of graphs, such as line graphs and bar charts. In a line graph, for instance, each plotted point represents a data value at a specific time, and connecting these points with lines illustrates trends over time. This is particularly useful in fields like finance, where tracking stock prices over days, months, or years can inform investment strategies.Furthermore, in statistics, the concept of plotted points extends beyond mere visualization. Statistical models often rely on the distribution of these points to make predictions. For example, in regression analysis, the goal is to find the best-fitting line through a set of plotted points. This line, known as the regression line, helps predict future values based on existing data. The closer the plotted points are to the regression line, the more reliable the predictions will be.In conclusion, the significance of plotted points in data analysis cannot be overstated. They serve as the foundation for understanding relationships between variables, identifying trends, and making predictions. Whether in academic research, business analytics, or everyday decision-making, mastering the interpretation of plotted points is an invaluable skill. As we continue to navigate an increasingly data-driven world, our ability to analyze and draw conclusions from these visual representations will be paramount to success.

在数学和数据可视化的世界中，术语plotted point指的是图表上表示特定值或一组值的特定位置。理解如何解读这些点对于分析趋势和根据数据做出明智的决策至关重要。例如，当我们创建散点图以显示两个变量之间的关系时，每个plotted point对应于这些变量值的交点。这种视觉表示使我们能够快速辨别数据集中的模式、相关性和异常值。考虑一个研究者研究运动对减肥影响的场景。通过收集一组参与者的数据，他们可以创建一个散点图，将“每周锻炼小时数”放在x轴上，将“减掉的磅数”放在y轴上。每个参与者的数据将由一个plotted point表示，使研究者能够观察不同锻炼水平与减肥之间的关系。如果这些点聚集成一条直线，这表明存在正相关；随着锻炼的增加，减肥也往往会增加。此外，每个plotted point的位置可以揭示重要的见解。例如，如果大多数点位于一条直线附近，但有几个远离这条线，这些离群值可能表示特殊情况或数据收集中的错误。理解这些plotted points帮助研究者完善他们的假设，并提高结论的准确性。除了散点图，plotted points在其他类型的图表中也至关重要，例如折线图和条形图。在折线图中，每个plotted point代表特定时间的数据值，连接这些点的线条展示了随时间变化的趋势。这在金融等领域特别有用，因为跟踪股票价格在几天、几个月或几年内的变化可以为投资策略提供信息。此外，在统计学中，plotted points的概念不仅仅局限于可视化。统计模型通常依赖这些点的分布来做出预测。例如，在回归分析中，目标是找到通过一组plotted points的最佳拟合线。这条线称为回归线，有助于根据现有数据预测未来值。plotted points越接近回归线，预测的可靠性就越高。总之，plotted points在数据分析中的重要性不容小觑。它们作为理解变量之间关系、识别趋势和进行预测的基础。无论是在学术研究、商业分析还是日常决策中，掌握对plotted points的解读都是一项宝贵的技能。随着我们继续在一个越来越依赖数据的世界中航行，我们分析和从这些视觉表示中得出结论的能力将是成功的关键。