Psychology Statistics for Dummies

The quick, easy way to master all the statistics you'll ever need The bad news first: if you want a psychology degree you'll need to know statistics. Now for the good news: Psychology Statistics For Dummies. Featuring jargon-free explanations, step-by-step instructions and dozens of real-life examples, Psychology Statistics For Dummies makes the knotty world of statistics a lot less baffling. Rather than padding the text with concepts and procedures irrelevant to the task, the authors focus only on the statistics psychology students need to know. As an alternative to typical, lead-heavy statistics texts or supplements to assigned course reading, this is one book psychology students won't want to be without. Ease into statistics – start out with an introduction to how statistics are used by psychologists, including the types of variables they use and how they measure them Get your feet wet – quickly learn the basics of descriptive statistics, such as central tendency and measures of dispersion, along with common ways of graphically depicting information Meet your new best friend – learn the ins and outs of SPSS, the most popular statistics software package among psychology students, including how to input, manipulate and analyse data Analyse this – get up to speed on statistical analysis core concepts, such as probability and inference, hypothesis testing, distributions, Z-scores and effect sizes Correlate that – get the lowdown on common procedures for defining relationships between variables, including linear regressions, associations between categorical data and more Analyse by inference – master key methods in inferential statistics, including techniques for analysing independent groups designs and repeated-measures research designs Open the book and find: Ways to describe statistical data How to use SPSS statistical software Probability theory and statistical inference Descriptive statistics basics How to test hypotheses Correlations and other relationships between variables Core concepts in statistical analysis for psychology Analysing research designs Learn to: Use SPSS to analyse data Master statistical methods and procedures using psychology-based explanations and examples Create better reports Identify key concepts and pass your course

Effect of preventive primary care outreach on health related quality of life among older adults at risk of functional decline: Randomised controlled trial

Objective: To evaluate the impact of a provider initiated primary care outreach intervention compared with usual care among older adults at risk of functional decline. Design: Randomised controlled trial. Setting: Patients enrolled with 35 family physicians in five primary care networks in Hamilton, Ontario, Canada. Participants Patients: were eligible if they were 75 years of age or older and were not receiving home care services. Of 3166 potentially eligible patients, 2662 (84%) completed the validated postal questionnaire used to determine risk of functional decline. Of 1724 patients who met the risk criteria, 769 (45%) agreed to participate and 719 were randomised. Intervention: The 12 month intervention, provided by experienced home care nurses in 2004-6, consisted of a comprehensive initial assessment using the resident assessment instrument for home care; collaborative care planning with patients, their families, and family physicians; health promotion; and referral to community health and social support services. Main outcome measures: Quality adjusted life years (QALYs), use and costs of health and social services, functional status, self rated health, and mortality. Results: The mean difference in QALYs between intervention and control patients during the study period was not statistically significant (0.017, 95% confidence interval -0.022 to 0.056; P=0.388). The mean difference in overall cost of prescription drugs and services between the intervention and control groups was not statistically significant, (-$C165 (£107; €118; $162), 95% confidence interval -$C16 545 to $C16 214; P=0.984). Changes over 12 months in functional status and self rated health were not significantly different between the intervention and control groups. Ten patients died in each group. Conclusions: The results of this study do not support adoption of this preventive primary care intervention for this target population of high risk older adults. Trial registration: Clinical trials NCT00134836.

The effects and side-effects of statistics education: Psychology students’ (mis-)conceptions of probability

In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists’ prediction who propose that education reduces misconceptions in general. They also predict that students with higher cognitive ability and higher need for cognition are less susceptible to biases. In Experiments 1 and 2 we found that the equiprobability bias increased with statistics education, and it was negatively correlated with students’ cognitive abilities. The representativeness heuristic was mostly unaffected by education, and it was also unrelated to cognitive abilities. In Experiment 3 we demonstrated through an instruction manipulation (by asking participants to think logically vs. rely on their intuitions) that the reason for these differences was that these biases originated in different cognitive processes.