Before we collect any data, I ask the students to write down their own hypothesis at the top of the A4 graph paper. The line of best fit passes through each of the points.Ĭreating Scatter Graphs from Primary DataĪs an extended plenary I challenge the students to create a scatter graph based on their own hand and foot size. In my experience, there are three main misconceptions when drawing lines of best fit. It is noted in several examiners reports by AQA and Edexcel that students are more likely to correctly estimate the value of a missing data point and identify anomalous data points if they use a line of best fit. The line of best fit also helps to predict the value of one variable when the other is known. We discuss the strength of the correlation as an indication of how closely two variables are related. The closer the points are to the line of best fit the stronger the correlation. Line of Best FitĪ line of best fit can be used to clearly illustrate the directional trend of the data. If two variables are not related the points will be scattered so no correlation is apparent. A negative correlation means as one variable increases the other will decrease.A positive correlation means as one variable increases, or decreases, so does the other.When we have plotted the points, I introduce the term correlation as a means to describe the relationship between two variables. In later examples on plotting scatter graphs and understanding correlation I expect students to choose and draw their own axes on A4 graph paper with appropriate scaling. I ask the class to sketch on their mini-whiteboards what the scatter graph might look like if our hypothesis is correct.įor the first couple of examples I provide the scaled axes for the class. The consensus is the more time people spend reading the less time they are likely to spend watching TV. The new descriptions of strength, linearity and direction.Plotting Scatter Graphs and Understanding CorrelationĪs we begin the first example we discuss the type of relationship we expect to see when time spent reading is plotted against time spent watching TV for a sample of ten people. Given a new set of scatterplots below, repeat the same exercise, but now with Portland, OR) there is a strong, linear trend. Though there are a few outliers (citiesĪlong the northwest coast of the US that have temperate winters, such as Negative direction, as the greater the latitude, the colder the Scatter plots are described as linear orįor example, the scatterplot of latitude and January temperatures had The linearity of scatter plot indicates how close the points are If the points are clearly clustered, or closelyįollow a curve or line, the relationship is described as strong. The more spread out the points are, the weaker The strength of a scatter plot is usually described as weak, Increases, or the points of the scatterplot go down from left to The explained variable decreases as the explanatory variable Increases as the explanatory variable increases, or the points of the The direction is positive when the explained variable The direction of a scatter plot can be described as positive or When describing the shape of the scatter plot and the relationshipīetween the explanatory and explained variable, there are three important This exercise would be simpler given uniform adjectives that everyone could Similarly, drivers with less driving experience are considered riskier and pay greater premiums. Ĭorrect: Drivers with more driving experience are considered safer, so they pay smaller premiums.(y) is the insurance premium paid for a sample of drivers. Q-6: The explanatory variable (x) is the years of driving experience and the explained variable
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