Hockenbury Discovering Psychology 5th txtbk

A-2 APPENDIX A Statistics: Understanding Data© Dan Piraro. Reprinted with special permission of King Features Syndicate.health care practitioners. Another questionnairefocused on self-perceptions ofhealth and well-being. Here we rated ourmood, energy level, physical symptoms,and health in general. A lifestyle surveyrequested information about diet (howoften did we eat red meat? how manyservings of fruits and vegetables did weconsume a day?), exercise (how many timesper week did we do aerobic exercise?), andbehavior (such as cigarette smoking andconsumption of alcoholic beverages). Thelifestyle survey also assessed psychologicalvariables such as levels of stress and happinessand how well we felt we were coping.At our first meeting with the researchers,we handed in the questionnaires and weretold which of the three groups we hadbeen assigned to. We returned early thenext morning to have our blood pressureand weight measured and to have blooddrawn for tests of our levels of cholesterol,triglycerides, and glucose. The two interventiongroups also received a weekend oftraining in their respective programs. Inaddition to daily practice of the techniquesthey had been taught, people in the traditionaland alternative groups were expectedto maintain a “compliance diary”—a dailyrecord of their exercise, diet, and relaxation/meditation activities. The purpose of thisdiary was to determine whether health outcomeswere better for people who practicedthe techniques regularly. At first I was disappointedwhen I was randomly assigned tothe control group because I was especiallyinterested in learning the alternative techniques.However, I was relieved later when Ifound out how much detailed record keepingthe intervention groups had to do!The researchers accumulated even moredata over the yearlong period. Every 3months, our blood pressure and weightwere measured. At 6 and 12 months, theresearchers performed blood tests andasked us to fill out questionnaires identicalto those we’d completed at the beginningof the project.The study included many variables.The most important independent variable(the variable that the researchermanipulates) was group assignment: traditionalprogram, alternative program, orno-treatment control. The dependentvariables (variables that are not directlymanipulated by the researcher but thatmay change in response to manipulationsof the independent variable) includedweight, blood pressure, cholesterol level,self-perceptions regarding health, andmood. Since the dependent variableswere measured several times, theresearchers could study changes in themover the course of the year.This study can help to answer importantquestions about the kinds of programsthat tend to promote health. But the purposeof describing it here is not just to tellyou whether the two intervention programswere effective and whether oneworked better than the other. In the nextcouple of sections, I will use this study tohelp explain how researchers use statisticsto (1) summarize the data they havecollected and (2) draw conclusions aboutthe data. The job of assessing what conclusionscan be drawn from the researchfindings is the domain of inferential statistics,which I’ll discuss later in this appendix.We’ll begin by exploring how researchfindings can be summarized in ways thatare brief yet meaningful and easy tounderstand. For this, researchers usedescriptive statistics.>> Descriptive StatisticsstatisticsA branch of mathematics used by researchersto organize, summarize, and interpret data.descriptive statisticsMathematical methods used to organizeand summarize data.The study of programs to promote health generated a large amount of data. Howdid the researchers make sense of such a mass of information? How did they summarizeit in meaningful ways? The answer lies in descriptive statistics. Descriptivestatistics do just what their name suggests—they describe data. There are manyways to describe information. This appendix will examine four of the most common:frequency distributions, measures of central tendency, measures of variability, andmeasures of relationships. Since I don’t have access to all the data that the healthpromotionresearchers gathered, I’ll use hypothetical numbers to illustrate these statisticalconcepts.