During а reseаrch meeting, yоu аnd yоur fellоw researchers decide to take a break. Although you try to make small talk, you find yourselves fishing for topics—that is, until someone starts reminiscing on their childhood video games, and brings up Guitar Hero III. Instantly, the room is abuzz with challenges and posturing. Initially, you claim that, as a kid, you probably beat more levels than anyone in the room (although secretly you remember, with self-loathing, an unsuccessful 2-hour marathon effort to defeat Slash in a primordial battle of guitar-shredding talent … you HATE that guy!). Sure enough, it turns out that a couple of your other classmates bested that top-hatted menace and moved on to higher levels. How will you ever again be able to hold your head up in research meetings? Now begins the inevitable cycle of self-criticism and despair, from which only ONE THING can save you … that’s right, STATISTICS!!! Perhaps, as they say, “practice does make perfect.” So, thinking quickly, you ask everyone in your group how many hours of Guitar Hero III they logged in in a week of childhood video game playing, along with the number of songs they have beaten (on medium, of course … you all still need time to actually do the reading for your classes!). Using these times and scores, you create the table below. Using these data, develop a regression equation that predicts how many songs you will be able to beat for a given number of hours-per-week practicing. WHEN YOUR NUMBERS INCLUDE DECIMALS, BE SURE TO ROUND TO TWO DECIMAL PLACES Student Hours (X) # of GH III Songs (Y) 1 2 7 2 72 39 3 47 12 4 59 16 5 15 11 Student (X) (Y) X Deviation Y Deviation Cross Product X Deviation2 Y Deviation2 1 2 7 [XDev_1] [YDev1] [CrossP1] [XDev2_1] [YDev2_1] 2 72 39 [XDev_2] [YDev2] [CrossP2] [XDev2_2] [YDev2_2] 3 47 12 [XDev_3] [YDev3] [CrossP3] [XDev2_3] [YDev2_3] 4 59 16 [XDev_4] [YDev4] [CrossP4] [XDev2_4] [YDev2_4] 5 15 11 [XDev_5] [YDev5] [CrossP5] [XDev2_5] [YDev2_5] Mean: [MeanX] [MeanY] ---------- Sum: [SumCross] [SumXDev] [SumYDev] Covariance: [Covariance] Sum of Squares X: [SSXreg] Sum of Squares Y [SSYreg] Variance X: [VarX] Variance Y: [VarY] Beta0: [Beta0] Beta1: [Beta1] Final Regression Equation: [RegressEquation] Elements of Regression Equation X = Each student’s individual scores on X Y = Each student’s individual scores on Y Deviation Scores: (X – Mean X) or (Y – Mean Y) Cross Product (X – Mean X) * (Y – Mean Y) Covariance (Sum of Cross Products)/n Deviation Squared (X – Mean X)2 or (Y – Mean Y)2 Sum of Squares (SSx or SSy) (Deviationx12 + Deviationx22 + Deviationx32 …) or (Deviationy12 + Deviationy22 + Deviationy32…) Variancex or Variancey SSx/n or SSy/n Beta1 Covariance/Variancex Beta0 Mean Y – (Beta1 * Mean X) Final Regression Equation Y = Beta0 + Beta1X
A precepting nurse is reviewing cоncepts оf the Gоod Sаmаritаn laws with a student nurse. Which of the following statements would demonstrate student understanding of the law?