Extended Mathematics 11 Statistics
Specific Curriculum Outcomes
DA01 Analyse, interpret, and draw conclusions from two-variable data using numerical, graphical, and algebraic summaries.
DA02 Critically analyze society’s use of inferential statistics.
DA03 Analyze data, identify patterns and extract useful information and meaning from large, professionally collected data sets.
DA01 Analyse, interpret, and draw conclusions from two-variable data using numerical, graphical, and algebraic summaries.
DA02 Critically analyze society’s use of inferential statistics.
DA03 Analyze data, identify patterns and extract useful information and meaning from large, professionally collected data sets.
DA01 Activities
- Hula Hoop and Starburst Scatterplots from Sarah Carter - Two activities for creating scatter plots and lines of best fit.
- Candle’s Burning 3-Act Task - Try to predict how long it will take for a candle to burn out. Linear relationships including classifying positive/negative, strong/weak, predicting via interpolation and extrapolation using a line of best fit on a scatter plot.
- Are Any of My Students Compatible? from Bob Lochel - Students “discover” the role of the correlation coefficient r – how it acts as a measure of the strength of the relationship between two quantitative variables in this activity.
- Charge Desmos Activity - In this activity, students use linear modeling to predict how long it will take for a smartphone to reach full charge. Students will also interpret the parameters of their equation in context.
- Guess the Correlation - the aim of the game is simple. try to guess how correlated the two variables in a scatter plot are. the closer your guess is to the true correlation, the better.
- Analyze a Linear Regression Line by Using Residual Analysis from Michelle Greene on LearnZillion - In this lesson students formally fit a least squares regression line to a set of data thought to be linearly associated. After determining the least squares regression line, students find residuals and create a residual plot to assess the linearity of the relationship between two quantitative variables.
- A Brief History of the Scatter Plot - The scatter plot has been called the most “generally useful invention in the history of statistical graphics.” This article talks about the origins of this scatter plot and how it has been used to allow people to adeptly look at a large number of points on a scale and understanding their relationship.
- The Datasaurus Dozen - 13 datasets (the Datasaurus, plus 12 others) each have the same summary statistics to two decimal places, while being drastically different in appearance. This shows why it is important to visualize data and not just rely on a statistical summary.
DA02 Activities
- Our Wold in Data - Explore the ongoing history of human civilization at the broadest level, through research and data visualization.
- How to Spot a Misleading Graph a TED-Ed video from Lea Gaslowitz - When they’re used well, graphs can help us intuitively grasp complex data. But as visual software has enabled more usage of graphs throughout all media, it has also made them easier to use in a careless or dishonest way — and as it turns out, there are plenty of ways graphs can mislead and outright manipulate. Lea Gaslowitz shares some things to look out for in this short 4 minute TED-Ed video.
- Data Viz Project - The Data Viz Project has a collection of data visualizations, searchable and sortable by shape, input, function, and family, each with real-world examples.