The new descriptions of strength, linearity and direction. 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
NO ASSOCIATION SCATTER PLOT DRIVERS
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. Using this line, we can predict how much money Mateo will earn in his 20th week of work (assuming he continues this pattern).īased on this line, Mateo will earn approximately $157 in week 20.Q-6: The explanatory variable (x) is the years of driving experience and the explained variable strong, nonlinearNegative, moderate, linearNo relationshipPositive, strong, linear. If there is a point that is much higher or lower (an outlier), it shouldn't be on the line. When describing the shape of the scatter plot and the relationship. For each of the given scatterplots, determine whether the plotted points appear to have positive, negative, or no correlation. When drawing the line, you want to make sure that the line fits with most of the data. The line we draw through the points on the graph just needs to look like it fits the trend of the data. So r close to 0 does not imply no relation, just no linear relation. or negative association, linear association, and non-linear association. A SCATTER DIAGRAM is a graph that shows the relationship between two quantitative. There are many complicated statistical formulas we could use to find this line, but for now, we will just estimate it. SP.1 Construct and interpret scatter plots for bivariate measurement data to. We use a "line of best fit" to make predictions based on past data. Mateo's scatter plot has a pretty strong positive correlation as the weeks increase his paycheck does too. Video game scores and shoe size appear to have no correlation as one increases, the other one is not affected. No Correlation: there is no apparent relationship between the variables.Time spent studying and time spent on video games are negatively correlated as your time studying increases, time spent on video games decreases. Negative Correlation: as one variable increases, the other decreases.Height and shoe size are an example as one's height increases so does the shoe size. Positive Correlation: as one variable increases so does the other.There are three types of correlation: positive, negative, and none (no correlation). With scatter plots we often talk about how the variables relate to each other. Maybe his father is giving him more hours per week or more responsibilities. For example, with this dataset, it is clear that Mateo is earning more each week. Using this plot, we can see that in week 2 Mateo earned about $125, and in week 18 he earned about $165.
In general, the independent variable (the variable that isn't influenced by anything) is on the x-axis, and the dependent variable (the one that is affected by the independent variable) is plotted on the y-axis. The weeks are plotted on the x-axis, and the amount of money he earned for that week is plotted on the y-axis. Here's a scatter plot of the amount of money Mateo earned each week working at his father's store: These types of plots show individual data values, as opposed to histograms and box-and-whisker plots. Scatter plots are an awesome way to display two-variable data (that is, data with only two variables) and make predictions based on the data.
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