![]() (The X key is immediately left of the STAT key). To graph the best-fit line, press the “Y=” key and type the equation –173.5 + 4.83X into equation Y1.Press the ZOOM key and then the number 9 (for menu item “ZoomStat”) the calculator will fit the window to the data.For Mark: it does not matter which symbol you highlight.For TYPE: highlight the very first icon which is the scatterplot and press ENTER.On the input screen for PLOT 1, highlight On, and press ENTER.We are assuming your X data is already entered in list L1 and your Y data is in list L2.Graphing the Scatterplot and Regression Line For now, just note where to find these values we will discuss them in the next two sections. The two items at the bottom are r 2 = 0.43969 and r = 0.663. Scroll down to find the values a = –173.513, and b = 4.8273 the equation of the best-fit line is ŷ = –173.51 + 4.83 x. ![]() For now, we will focus on a few items from the output and will return later to the other items. The output screen contains a lot of information. On the next line, at the prompt β or ρ, highlight “≠ 0” and press ENTER.On the LinRegTTest input screen enter: Xlist: L1 Ylist: L2 Freq: 1.(Be careful to select LinRegTTest, as some calculators may also have a different item called LinRegTInt). On the STAT TESTS menu, scroll down with the cursor to select the LinRegTTest.(If a particular pair of values is repeated, enter it as many times as it appears in the data). In the STAT list editor, enter the X data in list L1 and the Y data in list L2, paired so that the corresponding ( x, y) values are next to each other in the lists.USING THE TI-83, 83+, 84, 84+ CALCULATOR Using the Linear Regression T Test: LinRegTTest Interpretation: For a one-point increase in the score on the third exam, the final exam score increases by 4.83 points, on average.Slope: The slope of the line is b = 4.83.Interpretation of the Slope: The slope of the best-fit line tells us how the dependent variable ( y) changes for every one-unit increase in the independent ( x) variable, on average. You should be able to write a sentence interpreting the slope in plain English. It is important to interpret the slope of the line in the context of the situation represented by the data. The slope of the line, b, describes how changes in the variables are related. You should NOT use the line to predict the final exam score for a student who earned a grade of 50 on the third exam, because 50 is not within the domain of the x-values in the sample data, which are between 65 and 75. You could use the line to predict the final exam score for a student who earned a grade of 73 on the third exam. ![]() If the scatter plot indicates that there is a linear relationship between the variables, then it is reasonable to use a best-fit line to make predictions for y given x within the domain of x-values in the sample data, but not necessarily for x-values outside that domain. Remember, it is always important to plot a scatter diagram first. ![]()
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