![]() High values of one variable occurring with low values of the other variable. A clear direction happens when there is either: High values of one variable occurring with high values of the other variable or low values of one variable occurring with low values of the other variable. The number of points Amelia scores per game goes up when she practices her jump shot more.Ī scatter plot shows the direction of a relationship between the variables. Yes, Amelia’s assumption appears to be correct. She records the following data: X (hours practicing jump shot)Ĭonstruct a scatter plot and state if what Amelia thinks appears to be true. She notices that the number of points she scores in a game goes up in response to the number of hours she practices her jump shot each week. She wants to improve to play at the college level. You can press WINDOW to see the scaling of the axes.Īmelia plays basketball for her high school. Press the ZOOM key and then the number 9 (for menu item “ZoomStat”) the calculator will fit the window to the data.Make sure there are no other equations that could be plotted.For Mark: it does not matter which symbol you highlight, but the square is the easiest to see.For Xlist:, enter L1 ENTER and for Ylist: L2 ENTER.For TYPE: highlight the very first icon, which is the scatter plot, and press ENTER.On the input screen for PLOT 1, highlight On and press ENTER. Press 2nd STATPLOT ENTER to use Plot 1.Enter your X data into list L1 and your Y data into list L2.Scatter plot showing the number of m-commerce users (in millions) by year. Table showing the number of m-commerce users (in millions) by year. Let x = the year and let y = the number of m-commerce users, in millions. For the years 2000 through 2004, was there a relationship between the year and the number of m-commerce users? Construct a scatter plot. Users can do everything from paying for parking to buying a TV set or soda from a machine to banking to checking sports scores on the Internet. M-commerce users have special mobile phones that work like electronic wallets as well as provide phone and Internet services. In this example, you will learn how to make a scatterplot of respondents, ratings of how happy and how funny they are.In Europe and Asia, m-commerce is popular. Click here for more information on dealing with outliers in your data.Įxample 1: Creating scatterplots in Excel 2016 on There are no hard and fast rules regarding outliers, so the key is just to identify points which may potentially alter your results. Outliers may be points with different values for the outcome than the data with similar values for the predictor, or are farther out on the horizontal axis than the rest of the data. ![]() This point is visually not a part of the larger swath of data. In the first plot above, there appears to be an outlier at (26, 46). Outliers are points that do not follow the same general trend as the other points. The second plot shows no clear relationship, while the third shows a weaker linear relationship than the first plot (and in the opposition direction). Evidence of a linear relationship is important to confirm before conducting analyses such as correlation and regression.įinally, we can find the presence of outliers by viewing a scatterplot. We can also tell from a scatterplot whether or not there is a linear relationship between two variables, and if so, how strong that relationship is by looking at how tightly packed the points are around the trendline. Of the three plots above, the first shows the strongest linear relationship between the variables. The outcome variable is what we want to explain or predict based on the value of the predictor variable. Several examples are below:īy looking at a scatterplot, we can quickly determine the direction of the relationship between the two variables. If increases in the predictor variable tend to be associated with increases in the outcome variable (the points flow from the lower left to the upper right, like in the first plot), then the two variables are positively related. If increases in the predictor variable tend to be associated with decreases in the outcome variable (like in the third plot), then the variables are negatively related. The middle plot has no clear direction, so there is likely no actual relationship between the length of someone’s first name and how many hours they slept last night. In a scatterplot, the predictor, or independent variable, is located on the horizontal axis and the outcome, or dependent variable, is located on the vertical axis. A scatterplot is a tool for visualizing the association between two numeric variables. ![]()
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