practice - For the following data:... compute the mean,...

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Unformatted text preview: For the following data:... compute the mean, median, and major mode of dataset A, treating it as a sample compute the range, I.Q. range, M.A.D., variance, and standard deviation of dataset A as a sample compute the correlation between the data sets (treating columns as pairs) determine the least squares linear regression equation treating dataset A as the X variable predict the value of dataset B if dataset A is 16 and give a standard error of the estimate Dataset A: 25 13 25 27 14 17 29 15 25 13 20 Dataset B: 22 28 19 13 17 13 27 19 14 14 16 For the following data:... compute the mean, median, and major mode of dataset A, treating it as a sample compute the range, I.Q. range, M.A.D., variance, and standard deviation of dataset A as a sample compute the correlation between the data sets (treating columns as pairs) determine the least squares linear regression equation treating dataset A as the X variable predict the value of dataset B if dataset A is 16 and give a standard error of the estimate Dataset A: 25 13 25 27 14 17 29 15 25 13 20 Dataset B: 22 28 19 13 17 13 27 19 14 14 16 Averages: Sorted Data: 13 13 14 15 17 20 25 25 25 27 29 Major Mode: 25 Median: midpoint is datum number ( n + 1) / 2 = 6, median is 20 Mean: x = x n = 223 . 00 / 11 = 20.27 Variability: Variance and Standard Deviation: SS = summationdisplay ( x 2 )- ( x ) 2 n = 4893- 49729 11 = 372 . 18 s 2 = SS n- 1 = 37.22 , s = 6.10 M.A.D. = | x- x | n = 5.39 Sorted Data: 13 13 14 15 17 20 25 25 25 27 29 Range: max - min = 29 - 13 = 16 Interquartile range: n + 1 4 = 3 so count off 3 , 25- 14 = 11 Correlation and Prediction: Correlation: SP xy = summationdisplay ( xy )- ( x )( y ) n = 4119 . 00- (223 . 00)(202 . 00) 11 = 23 . 91 SS y = summationdisplay ( y 2 )- ( y ) 2 n = 3994- 40804 11 = 284 . 55 SS x = summationdisplay ( x 2 )- ( x ) 2 n = 4893- 49729 11 = 372 . 18 r = SP xy radicalbig SS x SS y = 23 . 91 radicalbig (372 . 18)(284 . 55) = 0.07 Regression: b = radicalbigg SS y SS x ( r ) = radicalbigg 284 . 55 372 . 18 (0 . 07) = 0 . 06 Y = y n = 202 . 00 / 11 = 18 . 36 , X = x n = 223 . 00 / 11 = 20 . 27 a = Y- ( b )( X ) = 18 . 36- (0 . 06)(20 . 27) = 17 . 06 Y prime = bX + a = Y prime =(0.06)(X)+(17.06) Prediction: at x = 16, the prediction for y = (0 . 06)(16) + 17 . 06 = 18.09 Standard Error of Prediction: s y | x = radicalBig SS y (1- r 2 ) n- 2 = radicalBig 284 . 55(1- (0 . 07) 2 ) 11- 2 = 5.61 Note: On the exam you should round all intermediate results to 2 decimal places. However the final answers on this key were computed using higher precision, therefore there may be rounding discrepancies with solutions computed rounding at every step, especially for prediciton. For the following data:......
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This note was uploaded on 02/06/2010 for the course PSYC psych 60 taught by Professor Federico during the Fall '09 term at UCSD.

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practice - For the following data:... compute the mean,...

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