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Quantitative

Quiz yourself by thinking what should be in each of the black spaces below before clicking on it to display the answer.
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Answer
independent variables   researcher manipulates/researcher can assign you/ cause (not result)  
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dependent variable   measuring behavior/ result (not cause)  
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correlation   2 variables that are related  
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population   complete collection of anything regardless of size  
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sample   subset of population/ measure so we can talk about population  
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parameter   numerical summary characteristics of a population stuff you can measure about a population  
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statistics   numerical summary of characteristics of a sample  
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nominal scale (scale of measurement)   assigns names or label to objects or events not related numerically just assigned  
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ordinal scale (scale of measurement)   puts objects/events in RANK order the difference btwn 1&2 doesn't mean anything just the order is meaningful  
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interval (scales of measurement)   equal intervals btwn numbers rank & equal distance zero isn't true zero, its a point on a scale  
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ration (scales of measurement)   zero means absence of what your measuring true zero absolute 0 degrees K no heat height 0.00 inches quantity/time  
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frequency distribution   create a table of the data gives organization table shows # of times a given score/ group of score occurs  
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rules of graphing   x= variable being studied y-axis=should be 3/4 the the length of the x-axis *always be divided using full range of frequency *always begin y-axis at zero *if your using top half, indicate a break  
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bargraph   histogram but bars dont touch  
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histogram   depicts grouped frequency distribution  
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grouped frequency distribution   range grouped data  
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central tendency   trying to come up with 1 number to describe variables mode mean median  
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mode   most frequently occurring score in a group of scores x  
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median   score that separates top half of group of scores from bottom half normal curve-median & mode in same place *data has to be in order middle score  
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percentile   score at or below which a given percentage of the scores lie 50th percentile: 50% of score are below that score  
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mean   arythmetic average/ sum of scores divided by number of scores (sum)(x-score)/N-number  
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mean properties   if you take all score the sum of the difference between each score and mean will be 0 sum of squared differences btwn each score from mean will be smaller than sum of squared diff. of any score 1,2,3,4,5 5-3=2 4-3=1 3-3=0 3-4=-1 3-5=-2  
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z-score   aka standard scores the deviation of the raw from the mean in standard deviation units z=raw score(x)-(mean)/SD  
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probability   the probability of event occurring is proportion of times event would occur if chance of occurrence were infinite  
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statistical hypothesis   hyp- guess about population based on sample results use probability theory to determine degree of certainty we have abt experimental results  
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2 rules of probability   1. each event independent from each other/ stand alone. necessary for simple probability 2. dice or coin dont have memory and cant remember or keep track  
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gamblers phallacy   (wrong belief) mistaken belief that probability of particular event changes with long strain of some event i.e. slot machines  
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addition rule   mutually exclusive random events compute the probability of one OR the other occurring P(A or B)= PA + PB 2 of spaids or 3 of clubs 1/52 + 1/52 = 2/52 = 1/56  
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multiplication rule   probability of 2 or more independent events occurring is the product of individual probabilities P rolling 2 ones (snake eyes) (1/6) (1/6) = 1/36  
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non independent events   *conditional probability drawing card and holding onto it draw ace and draw another one (4/52)(3/51)=1/221= .0045= .45% probability of second dependant on first  
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confidence interval   specific kind of interval estimate interval estimate of population can define by how "confident" compute a way to estimate things about a population  
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interval   range (set) of numbers  
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sampling distribution of mean   distribution of means of many samples u= mean of population  
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sampling distribution of mean (rules)   1. if you have infinite #, mean of means would be u 2. the more samples you get, the more the frequency graphs will look like normal curve 3. SD of means= standard error of mean 4. the larger each sample size, the smaller the standard error of mean  
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central limit theorem   the more samples you get, the more the frequency graphs will look like normal curve  
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t-score   how far a group mean is from population mean in standard error units  
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variable   anything that can take on different values or amounts  
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