PSY202-220189890
From PsychWiki - A Collaborative Psychology Wiki
Concepts:
Dependent Variable
Definiton- the variable that is being measured
Example- http://www.newsweek.com/id/101079
App: In this study, the variable being measured is men's IQ level
Nominal Variable
Definition: are mutually exclusive and exhaustive categories differing in some qualitative aspect.
Example: http://www.benjerry.com/flavors/our-flavors/#
App: The following are the flavors ben and jerry's offers for ice cream. Each flavor is mutually exclusive for the ice cream category
Ordinal Variable
Def: has the properties of a nominal scale, but in addition the observations may be ranked in order of magnitude (with nothing implied about the difference bettween adjacent steps on the scale)
Example: http://www.justsharethis.com/top-10-richest-person-in-the-world-2009/
App: This shows the richest people in the world from highest to lowest net worth
Interval Variable
Def: has all the properties of an ordinal scale and a given distance between measures has the same meaning anywhere on the scale
Ex: http://news.yahoo.com/s/ap/us_weatherpage_weather
App: In this article they state how temperatures range at a constant level between two numbers
Ratio Variable
Def: has all the properties of an intercal scale plus an absolute zero point
Ex: http://news.yahoo.com/s/nm/20091207/hl_nm/us_teen_stis
App: In this article it states that within 2 years of first having sex, the ratio of half of teenage girls may be 1 out of 3 sexually transmitted infections.
Frequency Distribution (regular, grouped, relative, or cummulative)
Def: shows the number of observations for the possible categories or score values in a data set.
Ex: http://sports.yahoo.com/nba/scoreboard
App: This site shows a frequency distribution of the scores in each of the four quarters of each basketball team.
Percentile (percentile or percentile rank)
Def: the percentage of cases in a distribution that falls below a given point on the measurement scale
Ex: http://sports.yahoo.com/nba/stats/bycategory?cat=Fielding&sort=23
App: This website shows the percentage of free throws made by each basketball player
Histogram
Def: a graph that consists of a series of rectangles, the heights of which represent frequency or relative frequency
Ex: http://www.stat.psu.edu/online/program/stat800/01_turning/graphics/histogram.jpg
App: This shows a graph showing the math scores of students in SAT's in 2005
Frequency Polygon
Def: a graph that consists of a series of connected dots above the midpoint of each possible class interval (height of the dots corresponds to frequencey or relative frequency)
Ex: http://hawaii.hawaii.edu/math/Courses/Math100/Chapter4/HomeWork/HmWrk411.htm
App: This frequency polygon shows the world's 25 largest banks.
Bar Diagram
Def: used for qualitative data, a graph that is similar to a histogram, except that space appears between the rectangles.
App: This shows a bar diagram the percentage of browser usage between certain websites such as firefox, yahoo, and google.
Pie Chart
Def: used for qualitative data , area in any piece of the pie shows the relative frequency of a category
Ex: http://hawaii.hawaii.edu/math/Courses/Math100/Chapter4/HomeWork/HmWrk411.htm
App: This pie chart shows the external causes of death in the United States.
Mean
Def: the sum of all the scores divided by the total number of scores
Ex: http://www.nba.com/lakers/stats/
App: This shows the averages of each player on the Lakers basketball team
Median
Def: the value that divides the distribution into halves
Ex: http://www.realtor.org/research/research/nar_research_maps_msa
App: This map price report shows the markets median home prices in various areas within the U.S.
Mode
Def: the score that appears with the greatest frequency
Ex: http://www.health-res.com/EX/08-01-21/e-free-nutrition-facts-300.jpg
App: This shows that 20 mg would be the mode because it is that amount that shows up the most within this nutritional facts
Range
Def: the difference between the lowest score and the highest score in a distribution
Ex: http://www.nba.com/playerfile/kobe_bryant/career_stats.html
App: Looking at the statistics for Kobe Bryants basketball career you can find the range by subtracting the lowest number hes scored in a game from the highest number hes scored in a game to get the range.
Variance
Def: the mean if the squares of the deviation scores
Ex: http://www.ibm.com/developerworks/rational/library/mar06/cantor/
App: This shows different kinds of variance
Standard Deviation
Def: the square root of the variance
Ex: http://images.google.nl/imgres?imgurl=http://www.americaninvestment.com/americaninvestment/media/images/maturity_decision.PNG&imgrefurl=http://www.americaninvestment.com/investor-resources/investment-basics&usg=__yTxAi6QHiiIAeFLaY72T8dfSIHc=&h=337&w=565&sz=9&hl=nl&start=15&um=1&itbs=1&tbnid=I0Rx1bgDFhP9gM:&tbnh=80&tbnw=134&prev=/images%3Fq%3Dstandard%2Bdeviation%2Btrade%26hl%3Dnl%26sa%3DN%26um%3D1
App: This study relates annualized compound return to the annualized standard deviation.
Standard Scores (z-scores)
Def: states how far away a score is from the mean in standard deviation units; one type of standard score
Ex: http://www.scielo.br/scielo.php?pid=S0021-75572009000400007&script=sci_arttext&tlng=en
App: This study determined the presence of certain types of bacteria in the feces of school children. In studying this, they configured the BMI or body mass index of the children as z scores.
Scatterplot
Def: a graph of a bivariate distribution consisting of dots at the point of intersection of paired scores
Ex: http://www.genderpsychology.org/autogynephilia/ray_blanchard/autogynephilic_androphilic.html
App: The scatter plot shows the relationship between transexuals attraction to men versus transexuals attraction to women
Correlation (r)
Def: a measure of the degree of relationship between two variables
Ex: http://www.bmj.com/statsbk/11.dtl
App: This correlation shows the relationship between height and pulmonary anatomical dead space in 15 children
EXTRA CREDIT: Correlation does not equal causation
ex: http://www.healthguru.com/content/video/watch/102088/Coffee_Stunts_Childrens_Growth_Myth_or_Fact
App: The studies between the relationship of caffeine consumption for children will stunt their growth shows that because they are correlated doesnt mean they cause each other. Without knowing more about the research done, we cannot conclude whether young children drinking coffee will stunt their growth.
EXTRA CREDIT: Critically Evaluating Research
Guideline 7: Check that results are fairly represented in graphics or concluding statements.
Ex: http://media.juiceanalytics.com/images/blog/excel_databar_fixed.jpg
App: This chart is supposed to show vegetables consumed. This graph is highly misrepresemted for many reasons. Alrhough it has data the bars are shaded but fade at the end so its hard to see the amounts. Also, brussel sprouts intake shows as a zero but regarding the bar itself there shows data.
EXTRA CREDIT: Critically Evaluating Research
Guideline 8: Stand back and consider the conclusions
Ex:http://www.quackwatch.com/01QuackeryRelatedTopics/massage.html
App: This article states that the use of different type of massage therapy such as reiki can influence the progress of any disease. Although it has been shown from certain patients to be effective there is not enough proof to have a viable belief that it can actually do just that.
EXTRA CREDIT: Critically Evaluating Research
Guideline 2: Consider the source
Ex: http://www.quackwatch.com/01QuackeryRelatedTopics/massage.html
App: Although supported by the American Massage Therapy Association (AMTA) and Associated Bodywork and Massage Professionals (ABMP) the people who carry out and fund these studies and statements, there may be a potential bias seen here since they are the ones supporting it. But this could tie in with guideline 8 as well.
EXTRA CREDIT: Critically Evaluating Research
Guideline 3: Examine the sampling method
Ex: http://www.funjoint.com/polls.htm
App: These polls are clearly biased because it is an online poll. They arent using people chosen at random. People get to decide whether to be included or not. It is a voluntary response survey.
EXTRA CREDIT: Critically Evaluating Research
Guideline 5: Watch out for confounding variables
Ex: Abstract
PURPOSE: To evaluate the effects of dietary caffeine intake and withdrawal on cerebral blood flow (CBF), as determined from a randomized, blinded, placebo-controlled study.
MATERIALS AND METHODS: Twenty adults (16 men, four women; age range, 24-64 years) categorized as low (mean, 41 mg/d) or high (mean, 648 mg/d) caffeine users underwent quantitative flow-sensitive alternating inversion-recovery perfusion magnetic resonance (MR) imaging twice: 90 minutes after a dose of caffeine (250 mg) on one day and after a dose of placebo on another day (randomized counterbalanced design). Doses were preceded by 30 hours of caffeine abstinence to induce withdrawal in high caffeine users. Quantitative CBF maps were gray matter (GM)–white matter (WM) segmented and subjected to region-of-interest analysis to obtain mean CBF in WM, anterior circulation GM (AGM), and posterior circulation GM (PGM). By using two-way repeated-measures analysis of variance, regional CBF data were tested for within-subject differences between caffeine and placebo and for between-subject differences related to dietary caffeine habits. Linear regression was used to determine whether dietary caffeine use predicts CBF or CBF response to caffeine.
RESULTS: Caffeine reduced CBF (P ≤ .05) by 23% (AGM, PGM) and 18% (WM) in all subjects. Postplacebo (withdrawal) CBF in high caffeine users exceeded that in low users (P ≤ .05) by 31% (AGM) and 32% (WM) (PGM, not significant). Mean postcaffeine CBF reduction in AGM was 26% in high users versus 19% in low users (P ≤ .05; PGM and WM, not significant). Increasing caffeine consumption predicted higher CBF (P ≤ .05) in all regions: r = 0.79 (AGM), 0.57 (PGM), and 0.76 (WM). Dietary caffeine use did not predict CBF response to caffeine.
App: Dietary caffeine consumption and withdrawal are potential confounding variables in cerebral perfusion and functional MR imaging.
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