Graphing Data Sets In Exercises 17–32, organize the data using the indicated type of graph. Describe any patterns.


Engineering Degrees Use a time series chart to display the data shown in the table. The data represent the number of bachelor’s degrees in engineering (in thousands) conferred in the U.S. (Source: U.S. Deapartment of Education)

Verified step by step guidance

1. Step 1: Understand the problem. You are tasked with creating a time series chart to display the data provided in the table. A time series chart is a graph that shows data points at successive time intervals, typically with time on the x-axis and the variable of interest on the y-axis.
2. Step 2: Identify the variables. In this case, the x-axis will represent the years (2011 to 2019), and the y-axis will represent the number of engineering degrees conferred (in thousands). The data points are: (2011, 93.1), (2012, 98.7), (2013, 103.0), (2014, 109.0), (2015, 115.1), (2016, 123.9), (2017, 133.8), (2018, 140.7), (2019, 146.3).
3. Step 3: Plot the data points. On graph paper or using software, mark the years on the x-axis and the number of degrees on the y-axis. Ensure the scale is appropriate to fit all data points clearly. For example, the x-axis could range from 2011 to 2019, and the y-axis could range from 90 to 150 (in thousands).
4. Step 4: Connect the data points. Use a line to connect the points sequentially from 2011 to 2019. This will create the time series chart, showing the trend in the number of engineering degrees conferred over time.
5. Step 5: Analyze the pattern. Observe the graph for trends. In this case, the number of engineering degrees conferred appears to increase steadily over the years, indicating a positive trend in the data.

Key Concepts

Time Series Data

Time series data is a sequence of data points collected or recorded at successive points in time, often at uniform intervals. In this context, the data represents the number of engineering degrees conferred annually from 2011 to 2019. Analyzing time series data helps identify trends, seasonal patterns, and fluctuations over time.

Graphing Techniques

Graphing techniques involve visual representations of data to facilitate understanding and analysis. A time series chart, specifically, displays data points over time, allowing for easy identification of trends and patterns. Proper graphing techniques enhance clarity and can reveal insights that raw data may not immediately show.

Trend Analysis

Trend analysis is the practice of collecting information and attempting to spot a pattern or trend in the data over time. In the context of the engineering degrees data, trend analysis would involve examining the increase in degrees conferred from 2011 to 2019, helping to understand the growth in engineering education and its implications for the workforce.