# ERA153

 The flashcards below were created by user julidei on FreezingBlue Flashcards. Descriptive Statistics Summarize a data set Inferential Statistics reveal the larger group through the smaller group's characteristicsrepresentative samples Population all the members of a defined group Sample any subset of a populationworks for interval dataworks for ratio data Qualitative variables differ by category rather than by amount but there are measurable differences Constants never vary, hold little analytical value Variables they have different manifestations A Research Design formal plan for gathering and analyzing data Independent Variable the variable thought to affect another Dependent variable the variable influenced Data Scale different kinds of measures gauge different qualities Measurement using rules to asign numbers Nominal data indicate a category, yields the least amount of information about an object Ordinal data allows rankinggreater thanless thanpercentile scores Interval data indicates degree of difference Ratio data includes a zerouncommon in educational measurement Interval Scale Data how much greater or less Descriptive Statistics calculated so that one can know the essential characteristics of data sets without having to refer to each individual measure. Central tendency most typical in a data set Measures of Central Tendency mode, median, mean Mode most frequently occuring measure in a group Unimodal one mode bimodal two modes Median the point below which half the scores in the group occur.isn't calculated as much as it is identified.the middle most number Mean most commonly used measure of central tendency is the arithmetic average Outliers measures in a group that are so high or so low compared to the others that they will have an undue effect on the statistics. Range the difference between the highest and the lowest Quartiles Fourths of the range Interquartile Range stretches from the 25th to the 75th percentile in a distribution. Semi-interquartile Range half the interquartile range Variance the sum of the squared score to mean differences divided by n-1 Standard Deviation the square root of the variance Frequency Distribution data are displayed so that their variety and their frequency of occurrence are both apparent. Class Intervals grouping the data in a frequency distribution rather than listing them individually Apparent Limits represented by the lowest and highest integers in the category Actual Limits extend the interval up and down by 1/2 point Stem and Leaf Display or Stem Plots liar all values according to stem (the numbers preceding the final value) and leave (the final digit) Pie Charts and Bar Charts used to represent proportional differences in data categories either by triangular wedges or with bars of different sizes Quadrant graphs are created by vertical and horizongal ines which intersect at right angles. The four sections which result are each called a quadrant. Normal Distribution Gaussian Distribution takes on the bell shape because it is symmetrical and unimodal and the standard deviation is 1/6 of the range. Point of Inflection a normal curve moves outward more quickly than downward occurs at +/- one standard deviation from the mean positive skew when the mean is larger than the median negative skew when the mean is smaller than the median Kurtosis describes how much spread there is in a distributionskewnessdefines how bunched up the data is Mesokurtic Normal distributionstandard deviation is about 1/6 R Platykurtic distribution with too much variabilityStandard deviation is greater than 1/6 R Leptokurtic little variabilitystandard deviation is less than 1/6 R Standard Normal Distribution there is only one standard normal distribution Z transformation scores = 0standard deviation = 1 Modified Standard Score created so that it has a prespecifiied mean and standard deviation The Distribution of Sample Means population based on the means of samples rather than on individual scores. it allows one to determine whether a particular sample is likely to have been drawn from the specified population which is the z test Central Limit Theorem A population of sample means will be normal even if the distribution of individual scores wasn't Sampling Error the difference between characteristics of the sample and those of the population law of large numbers indicates that error diminishes as sample size increases Standard Error of the Mean measure of variability in the distribution of sample means. It is the standard deviation of all the sample means that constitute the distribution of sample means. Statistically Significant that an outcome isn't likely to have occured by chance Alpha level the probability of incorrectly determining a statistically significant resultoccurs if when the null hypothesis is erroneously rejected.if further testing with new data indicates that the initial finding of statistical significance was in errror, an alpha error occured with that first test. Type II or Beta error occurs when one incorrectly concludes that a result isn't statistically significant. Confidence Intervals for Z intervals within which the population mean represented by a sample will probably occur. stastistics v. parameters characteristics of sample v characteristics of population Authorjulidei ID135003 Card SetERA153 Descriptionterms from the book Updated2012-02-13T22:44:26Z Show Answers