{"id":471,"date":"2022-05-18T16:39:48","date_gmt":"2022-05-18T16:39:48","guid":{"rendered":"https:\/\/pressbooks.ccconline.org\/accintrostats\/chapter\/scatter-plots\/"},"modified":"2022-08-10T19:37:10","modified_gmt":"2022-08-10T19:37:10","slug":"scatter-plots","status":"publish","type":"chapter","link":"https:\/\/pressbooks.ccconline.org\/accintrostats\/chapter\/scatter-plots\/","title":{"raw":"Chapter 3.3: Scatter Plots","rendered":"Chapter 3.3: Scatter Plots"},"content":{"raw":" \r\n\r\nBefore we take up the discussion of linear regression and correlation, we need to examine a way to display the relation between two variables x<\/em> and y<\/em>. The most common and easiest way is a scatter plot<\/strong>. The following example illustrates a scatter plot.\r\n
\r\n\r\nIn Europe and Asia, m-commerce is popular. M-commerce users have special mobile phones that work like electronic wallets as well as provide phone and Internet services. 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. For the years 2000 through 2004, was there a relationship between the year and the number of m-commerce users? Construct a scatter plot. Let x<\/em> = the year and let y<\/em> = the number of m-commerce users, in millions.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Table showing the number of m-commerce users (in millions) by year.<\/caption>\r\n
\\(x\\) (year)<\/th>\r\n\\(y\\) (# of users)<\/th>\r\n<\/tr>\r\n<\/thead>\r\n
2000<\/td>\r\n0.5<\/td>\r\n<\/tr>\r\n
2002<\/td>\r\n20.0<\/td>\r\n<\/tr>\r\n
2003<\/td>\r\n33.0<\/td>\r\n<\/tr>\r\n
2004<\/td>\r\n47.0<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
\r\n
Scatter plot showing the number of m-commerce users (in millions) by year.<\/div>\r\n\"This<\/span>\r\n\r\n<\/div>\r\n<\/div>\r\n
\r\n\r\nTo create a scatter plot:\r\n
    \r\n \t
  1. Enter your X data into list L1 and your Y data into list L2.<\/li>\r\n \t
  2. Press 2nd STATPLOT ENTER to use Plot 1. On the input screen for PLOT 1, highlight On and press ENTER. (Make sure the other plots are OFF.)<\/li>\r\n \t
  3. For TYPE: highlight the very first icon, which is the scatter plot, and press ENTER.<\/li>\r\n \t
  4. For Xlist:, enter L1 ENTER and for Ylist: L2 ENTER.<\/li>\r\n \t
  5. For Mark: it does not matter which symbol you highlight, but the square is the easiest to see. Press ENTER.<\/li>\r\n \t
  6. Make sure there are no other equations that could be plotted. Press Y = and clear any equations out.<\/li>\r\n \t
  7. Press the ZOOM key and then the number 9 (for menu item \"ZoomStat\") ; the calculator will fit the window to the data. You can press WINDOW to see the scaling of the axes.<\/li>\r\n<\/ol>\r\n<\/div>\r\n
    \r\n
    Try It<\/div>\r\n
    \r\n
    \r\n\r\nAmelia plays basketball for her high school. She wants to improve to play at the college level. 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 records the following data:\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
    X<\/em> (hours practicing jump shot)<\/th>\r\nY<\/em> (points scored in a game)<\/th>\r\n<\/tr>\r\n<\/thead>\r\n
    5<\/td>\r\n15<\/td>\r\n<\/tr>\r\n
    7<\/td>\r\n22<\/td>\r\n<\/tr>\r\n
    9<\/td>\r\n28<\/td>\r\n<\/tr>\r\n
    10<\/td>\r\n31<\/td>\r\n<\/tr>\r\n
    11<\/td>\r\n33<\/td>\r\n<\/tr>\r\n
    12<\/td>\r\n36<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

    Construct a scatter plot and state if what Amelia thinks appears to be true.<\/p>\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\nA scatter plot shows the direction<\/strong> of a relationship between the variables. A clear direction happens when there is either:\r\n