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Hoàng Thị Bích Ngọc đang tìm kiếm từ khóa Which of the following statements is an accurate interpretation based on the graph được Update vào lúc : 2022-11-24 08:40:05 . Với phương châm chia sẻ Kinh Nghiệm Hướng dẫn trong nội dung bài viết một cách Chi Tiết 2022. Nếu sau khi tham khảo Post vẫn ko hiểu thì hoàn toàn có thể lại Comments ở cuối bài để Admin lý giải và hướng dẫn lại nha.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.
Nội dung chính Show- Example: Correlation Between Height and Weight
Section Example: Seatbelt Usage
Section Example: IQ Scores SectionOn this pageUsing sentence starters to analyse graphsUsing a framework to interpret graphs
The correct interpretation of a 95% confidence interval is that "we are 95% confident that the population parameter is between X and X."
Example: Correlation Between Height and Weight Section
At the beginning of the Spring 2022 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.
Example: Seatbelt Usage Section
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.
Example: IQ Scores Section
A random sample of 50 students 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 this school is between 96.656 and 106.422.
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Previous4.2 - Introduction to Confidence Intervals Next4.2.2 - Applying Confidence Intervals
On this page
- Using sentence starters to analyse graphsUsing a framework to interpret graphs
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:
- know how to interpret graphs
to elicit key informationextract the basic informationdraw conclusionscompare and contrast and
provide recommendations.
Individuals with higher levels of graphical literacy are better able to find information in graphs, and they spend more time looking 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:
- the importance of headingslabelling of axes scaling of axes (for example, linear or logarithmic) use of colourchoice of graph type (for example, pie chart, line graph, bar graph, column graph).
Two strategies to support students to interpret graphs are:
- using sentence starters using frameworks
Additional strategies to support students to read graphs can be found in 'Language for graphs and statistical displays'.
Using sentence starters to analyse graphs
Sentence 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:
- This graph shows …A pattern I notice in the graph is …An anomaly/outlier/different pattern in the graph is …A difference between … and
…. is …A similarity between … and … is If this pattern continued, I predict …A probable reason for that pattern is …A probable reason for this difference is …When I first looked this graph …The data that most stood out to me was …
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.
- This graph shows the types of drinks drunk by Australian children. A general pattern I notice in the graph is that as the child's age increases, they drink more of these kinds of drinks. A reason for this pattern
might be because older children can go out and buy their own drinks. A different pattern in the graph is that energy drinks go down for 14 to 16-year old. A reason for this pattern might be because they prefer drinking other drinks. The data that most stood out to me was that sports drinks were drunk more than soft drinks.
Using a framework to interpret graphs
In 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
This graph shows the estimated societal costs of alcohol misuse in Australia. The total estimated cost exceeds $14 billion. The largest cost relates to productivity, which accounted for 42.1% or $6.046 billion. Traffic accidents comprised 25.5% or a quarter of the costs ($3.662 billion). Alcohol misuse had the least cost to the health system, costing $1.686 billion.
Source: Surveillance of notifiable infectious diseases in Victoria, 2011–2014
This graph shows the number of notified cases of laboratory-confirmed cases of influenza in Victoria from 2011 to 2014. Each year, there is a spike in confirmed cases, which begins in June and lasts until October. This coincides with winter when people are more likely to be spending time indoors. The number of infected cases during the winter spike has also increased each year. In 2011, the peak number of infected cases was around 800 while in 2014, the peak number is just over 3000.
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