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In the future, researchers may be able to retrieve in electronic form data archives that include complex stimuli used in an experiment, videos of performance of the animal, interactive demonstrations of the procedure, and (of particular importance) the original raw data Design of Experiments Randomization is an important feature of experimental designs In experiments in which different groups of animals receive different treatments, the animals should be assigned to treatments at random No rm conclusions can be made from an experiment in which animals were assigned to treatments haphazardly because it is impossible to rule out the possibility that the assignment was made in a way that biased the results In experiments in which each animal receives all of the treatments, the order of treatments for each animal should be assigned at random.

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The social construction of premenstrual syndrome: A case study in scienti c discourse as cultural contestation In M G Winkler & L B Cole (Eds), The good body: Asceticism in contemporary culture (pp 91 107) New Haven, CT: Yale University Press Pyke, S W (1993) The more things change Canadian Psychology, 33, 2 Radloff, L S (1975) Sex differences in depression: The effects of occupation and marital status Sex Roles, 1, 249 265 Reid, P T (1993) Poor women in psychological research: Shut up and shut out Psychology of Women Quarterly, 17, 133 150 Rodin, J, Silverstein, L R, & Striegel-Moore, R H (1984) Women and weight: A normative discontent In T B Sonderegger (Ed), Psychology and gender: Nebraska Symposium on Motivation, 1984 (pp 267 307) Lincoln: University of Nebraska Press..

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No rm conclusion can be made from an experiment in which the order of treatments was selected haphazardly because it is impossible to rule out the possibility that the order of the treatments (such as the characteristics of the previous treatment) affected the performance on the current treatment..

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Aaron, L. A., 174, 185, 188 Aarons, S. J., 480, 482 Aaronson, N. K., 291 Abbott, P. J., 551, 559 Abbott, R. D., 565 Abbuhl, S., 541 Abdel-Moty, E., 313 Abel, G. G., 250, 263 Abel, J. L., 60, 69 Abeles, N., 500, 507, 508 Abenhaim, L., 594, 607 Ablashi, D., 372, 384, 386 Abou-Issa, H., 613 Abraham, M., 346, 359, 570 Abrahams, R., 532, 541 Abrams, A., 596, 609 Abrams, M., 57, 70 Abreu, J., 112, 116 Abrous, N., 163 Achenbach, T. M., 402, 408 Achterberg, J., 606, 608 Ackenheil, M., 189 Ackerman, K. D., 76, 90 Ackerson, L., 104, 115 Acquas, E., 151, 162 Adams, A., 594, 608, 613 Adams, D. C., 56, 73 Adams, G., 37, 45 Adams, J. H., 547, 560 Adams, P., 37, 45 Adams, S., 109, 114 Adams, T. A., 344, 359 Adams-Campbell, L. L., 546, 552, 559, 560 Adamson, K. L., 151, 163 Aday, L. A., 549, 561 Adelson, J., 468, 483, 484 Ader, R., 34, 39, 45, 85, 87, 93, 188, 372, 385 Adesso, V. J., 552, 565 Adkins, J. A., 425, 435, 569, 573, 574, 575, 576, 577, 578, 580, 582, 586, 588 Adkins, R., 425, 431 Adler, A. I., 550, 559, 561 Adler, A. J., 599, 608 Adler, C. S., 249, 263, 265 Adler, G. K., 172, 178, 185 Adler, L. E., 154, 162 Adler, N. E., 479, 482, 521, 528, 529, 536 Adler, S. M., 265 Adler, W. H., 78, 88 Adlis, S., 109, 117, 128, 141 Aebi, M., 313 Afari, N., 105, 106, 107, 108, 109, 110, 115, 119 Af eck, G., 52, 57, 58, 59, 66, 68, 73, 105, 109, 115, 173, 174, 176, 182, 185, 187, 188

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When there are large differences in variability among the numerical variables, the data analyst needs to apply standardization The transformations already applied do help in part to reduce the difference in variability among the variables, but substantial differences still exist For example, the standard deviation for the variable sqrt spending in the last six months is 1002, while the standard deviation for the variable sqrt # coupons used is 0735 To avoid the greater variability of the sqrt spending in the last six months variable overwhelming the sqrt # coupons used variable, the numeric elds should be normalized or standardized Here, we choose to standardize the numeric elds, so that they all have a mean of zero and a standard deviation of 1 For each variable, this is done by subtracting the mean of the variable and dividing by the standard deviation, to arrive at the z-score.

On the MT side of things, you will likely want to set up a new blog specifically for this purpose, following earlier instructions about how to set up a photo blog. You will also want to create an images directory off your archive directory into which pop2blog can place photos.

In this analysis, the resulting variable names are pre xed with a z (eg, z sqrt # coupons used) Other normalization techniques, such as min-max normalization, may be substituted for z-score standardization if desired Figure 79 shows the histogram of the variable z sqrt spending last one month Note the spike that represents the majority of customers who have not spent any money at the store in the past month.

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