Which of the following statements is an accurate interpretation based on the graph
Confidence intervals are often misinterpreted. The logic behind them may be a bit confusing. Remember that when we're constructing a confidence interval we are estimating a population parameter when we only have data from a sample. We don't know if our sample statistic is less than, greater
than, or approximately equal to the population parameter. And, we don't know for sure if our confidence interval contains the population parameter or not. The correct interpretation of a 95% confidence interval is that "we are 95% confident that the population parameter is between X and X." At the beginning of the Spring 2017 semester a sample of World Campus students were surveyed and asked for their height and weight. In the sample, Pearson's r = 0.487. A 95% confidence interval was computed of [0.410, 0.559]. The
correct interpretation of this confidence interval is that we are 95% confident that the correlation between height and weight in the population of all World Campus students is between 0.410 and 0.559. A sample of 12th grade females was surveyed about their seatbelt usage. A 95% confidence interval for the proportion of all 12th grade females who always wear their seatbelt was computed to be [0.612, 0.668]. The correct interpretation of this
confidence interval is that we are 95% confident that the proportion of all 12th grade females who always wear their seatbelt in the population is between 0.612 and 0.668. A random sample of
50 students at one school was obtained and each selected student was given an IQ test. These data were used to construct a 95% confidence interval of [96.656, 106.422]. The correct interpretation of this confidence interval is that we are 95% confident that the mean IQ score in the population of all students at this school is between 96.656 and 106.422. Graphs communicate important quantitative information in a visual format and are often used to communicate health and medical information. Much of the HPE curriculum involves students being presented with information in graphical form. Using this form of representation, students
must: Individuals with higher levels of graphical literacy are better able to find information in graphs, and they spend more time looking at conventional features of graphs to generate more accurate interpretations (Okan, Galesic & Garcia-Retamero, 2015). Teachers should explicitly teach the meaning-making (semiotic) systems of graphical representations before having students analyse graphs (see 'Explicitly teaching text structure' and 'Reading and unpacking visual representations of data' ). This includes explaining:
Two strategies to support students to interpret graphs are:
Additional strategies to support students to read graphs can be found in 'Language for graphs and statistical displays'. Using sentence starters to analyse graphsSentence starters are one way to scaffold students' interpretation of graphs. Sentence starters provide a focal point for students to begin writing (or saying) an interpretation of the data they are viewing in graphical form. Sentence starters can range in their cognitive demand, moving from identifying information and patterns in the graph to generating comparisons, predictions, and hypotheses. Sentence starters teachers can provide students include:
The example below provides some completed sentences a Year 7 or 8 student wrote after viewing a graph about the types of drinks consumed by Australian children
(VCHPEP129).
Source: Figure 3 in Boden Institute,
University of Sydney 2014. Evidence Brief Obesity: Sugar-Sweetened Beverages, Obesity and Health. Australian National Preventive Health Agency, Canberra.
Using a framework to interpret graphsIn HPE, students write with a specific purpose as they communicate their interpretations to others. Students aim to explain, critique, and analyse real-world data relating to health, well-being, and physical activity. As students become more capable of interpreting data on their own, they can be given frameworks to help structure independent analyses of graphs, whether spoken or written. One framework to use to analyse a graph is given below. Depending on the length of analysis and information in the graph, the framework could be used to create one paragraph or several.
Below are two
samples showing how a Year 9 or 10 student has applied the framework to interpret two different graphs (VCHPEP148).
Source: Manning, M., Smith, C., & Mazerolle, P. (2013). The estimated societal costs of alcohol misuse in Australia. Trends and Issues in Crime and Criminal Justice no. 454. Canberra: Australian Institute of Criminology Student sample response |