Why Do You Have to Take Statistics?

One of the reasons you are required to take Statistics is to provide you with the ability to comprehend the research being conducted in your major and to stay current with new theories and procedures within your profession. Following are excerpts taken from several professional journals: Justice Quarterly, Nursing Research, Developmental Psychology and Education Research. The statistical measures are highlighted in bold print. At this time, don't worry about understanding the articles or comprehending the statistics. However, by the completion of this course, you will possess an understanding of the significance of these statistical measures and their implications.

Justice Quarterly
"Impact of Shock Incarceration", by Mackenzie and Shaw

A CHI-SQUARE analysis showed a significant difference among groups in types of new crimes arrests, CHI-SQUARE = 21.0, p < 0.007. As shown, the dropouts had more violent offenses than the other groups.

Nursing Research
"Dietary Fiber and Distressing Gastrointestinal Symptoms in Midlife Women", by Jane M. Georges and Margaret M. Heitkemper

Relationship of Fiber, Caffeine, and Alcohol Intake to GI Symptoms: There were significant CORRELATIONS between total dietary fiber, caffeine and alcohol intake (for 9 days of data collection) and the averages of specific distressing GI symptoms for each subject across 30 days. Significant negative relationships were noted between dietary fiber intake and nausea (r = -0.79, p < 0.001); abdominal pain (r = -0.69, p < 0.001); awakening with abdominal pain (r = -0.64, p < 0.002); awakening with rectal pain (r = -0.43, p < 0.05); and awakening with nausea (r = -0.68, p < 0./001). No significant relationships were noted between the amount of caffeine or alcohol intake and distressing GI symptoms.

Developmental Psychology
"Imaging the Outcome of Pretend Transformations: Assessing the Competence of Normal Children and Children with Autism" by Robert D. Kavanaugh and Paul L. Harris

Each child was scored for the number of items (out of six) on which he or she chose the correct Picture. Random performance would lead to three correct choices (our of six) by chance. The two age groups behaved quite differently. In the younger group, the majority of children made fewer than three correct choices, whereas in the older group, the majority made more than three correct choices. To assess overall performance by each age group, we used two separate t tests to compare the observed scores with chance performance. The younger group performed worse than chance t(14) = 4.30, p < 0.001, whereas the older group performed better than chance, t(14) = 5.56, p < 0.001. In addition a t test for independent sample confirmed that older children were more accurate than younger children, t(28) = 6.94, p < 0.001.

Educational Research
"Meta-Analysis of Word Processing", by Bangert and Drowns

Russell (1991) reported a meta-analysis of 21 studies of instruction involving word processing and keyboarding. Effect sizes in this review varied to extremes (low of -2 standard deviations to highs of 4.5 standard deviations), so median values would be the best indicators of central tendency. Median effect sizes for different types of writing outcomes hovered near zero: 0.09 for writing quality, 0.02 for revision, and -0.03 for attitude toward writing and computers. Russell noted that in cases where word processing seemed beneficial, the benefits may not be due at all to the word processing itself but to the kinds of social interactions that computer laboratory environments permit.