# Jessica

 Statistics is A branch of mathematics focused on *organization*analysis*interpretation of numbers goal of statistics to organize and interpret data Characteristics or conditions that can change. Variables(most research begins with a question about the relationship between 2 variables for a specific group of individuals.) The entire group of individuals is population examples of population * relationship between class size and academic performance for 3rd graders selected to represent the population (populations are usually so large that researchers cannot examine the entire group) Sample measurements obtained in a study Datat Two types of Statistical Methods *Descriptive statistics*Inferential statistics Organize and summarize data Descriptive statisticsexamples: * tables, grapshs, average score parameter a descriptive value for a population Statistic a descriptive value for a sample Use sample data to make general conclusions about population Inferential Statistics 1. a sample is only a part of the whole _____ 2. sample data provide limited info about the___ 3. sample statistics are imperfect representatives of the corresponding ___ parameters population the discrepancy between a sample statistic and its population parameter is called Sampling error 2 classifications of variables 1. discrete variables2. continuous variables discrete variables indivisible categoriesexamples*gender*car*sex infinitely dividable Continuous variablesexamples*height,pain, time, weight to establish relations between 2 variables... *Variables must be measured*Variables must be classified into one category 2 scales of measurement 1.nonimal scale2.ordinal scale3.interval scale4.ratio scale an unordered set of categories Nominal scaleexamples*gender*martial status an ordered set or categories Ordinal scale example *horse races, contests with places 1st, 2nd, 3rd an ordered series of equal-sized categories Interval scaleexamples*6-point likert scale (rate 1-10)*IQ An ordered series of equal-sized categories A value of zero indicates none of the variable Ratio Scale examples*lenth, volume 3 major classifications - experiemental studies-correlation studies-quasi-experiemetal studies one variable is manipulated IV a second variable is observed for changes DV all other variables are controlled to prevent them from influencing the results. Experimental Studies what is teh goal of experimental studies ? and give an example? to establish a cause-effect relationship between the IV and the DV - i.e., does noise decrease test scores amount of noise=IVtest scores=DVenvironment and time = controlled observe two variables as they exist naturally.. I.e., is high school GPA related to SAT scores? Correlation Studies similar to an experiment but is missing either the manipulated IV or the control necessary for a true experiment Quasi-experimental study- the IV is usually a pre-existing variable -i.e., parent child relationship, cancer. the number of scores with a value frequency the pattern of frequencies over different values frequency distribution frequency tables make sense of a set of numbers. show how many times a number is used bar graph. provide a picture of distribution histograms line graph frequency polygons a frequency distribution with 2 or more high points multimodal Negative Skew points to the left, peak is in the right. ceiling effects means what skew? and if the table was test grades what would the result tell you ceiling effect is a negative skew, most scores piled up at the right meaning the test was too easy. floor effect means what? and what a floor effect mean for a test? floor effect is a positive skew. most scores piled up at the left, meaning the test was too hard. a representative or typical value in a distribution Central Tendency 3 meausres of central tendency 1. mean2. median3.mode of the best measure of central tendency. most frequently reported in research articles think of the mean as the "balancy point" of distribution. Mean Middle value in a group of scores. half the scores are above, half the scores are below (aka the "50h percentile") Median- unafftected by extreme individual scores - unlike the mean prefereable as a measure of central tendency when a distribution has EXTREME scores or when SKEWED. most common single number in distribution. IF distribution is symmetrical and unimodal ____ = the mean - typical way of describing central tendency of a nominal variable Mode the second way to describe numbers Dispersion 3 measures of dispersion 1.range2.vairance3. standard deviation simpliest measure of dispersion. The distance from the lowest to the highest score Range how spreadout the scores are from the mean. variance another measure of variation. Roughly the average amount scores differ from the mean. used more widely than variance. standard diviation are standardized scores used to compare numbers from different distributions. describe particular scores. where a score fits in a group of scores in a distribution. Z scores- raw scores are meaningless. -i.e., i got a score of 565 in meaningless. vs, i got a z-score of 1.64 z scores continued. the sign of the z score (- or +) indeciateds. the score is located above the mean (+). or below the mean (-). the value of z indicates the number of standard deviation between x and the mean of distribution. -z score of 1.0 is one SD aboce the mean-z score of -2.5 is two and a half SDs below the mean-z score of 0 is AT the mean measure and describe the relationship between 2 variables Correlation- X = one score -y = other score pair of XYsocres is usually from the same subject descriptive statistic - single number (e.g. r=.78) - summarizes and describes a relationship correlation coefficient Coffee and nervousness, are correlation coefficient but they DONT ____ each other COEFFICIENTS DO NOT CAUSE EACH OTHER. need a true experiment as X scores increase, Y scores also increase positive linear relationship as X scores increase, Y scores decrease negative linear relationship as X scores increase, Y scores do NOT only increaseor only decrease. - at some point the Y scores change their direction of change non-linear relationships (curvilinear) The larger the absolute value of the correlation coefficient, the _____ the relationship Stronger. the sign only indicates the direction of the linear relationship, NOT the strength. i.e., .78 and -.78 are strong relationships describe relationships of 2 variables in a sample luck of the draw may produce a correlation, so you'll also need statistical significance. correlatoin coefficients only accept a correlation as "real" if it's significiant. "income was related to agression (r=-.78, p<.05). what does this tell you... that it is significant. that there is less than a 5% chacne that the correlation in a population is NOT REAL (which means a 95% chance that it is real) Research articles report: Correlation coefficientts : put single correlations _____ in text. i.e., there was a significant correlation (r=.51, p<.05) between age and depression. Research Articles Report: Correlation Coefficients, put several correlations ____ in table. (variables listed down left and across top) The correlation of each pair of variables is shown in tables the table is called a ____ Correlation Matrix Correlations help in making ____ predictions e.g., prediction college GPA from HS SAT what is the variable being predicted from predictor variable (X) whats the variable being predicted to criterion variable (Y) social scientists call prediction regression. - can predict using 2 scores or raw scores prediction using 2+ predictor variables is called multiple regression*** mutiple regression and correlation are frequently reported in research articles, so its important to have a general understanding of them. Authorjchampio ID62868 Card SetJessica DescriptionExam Chapters 1-3 Updated2011-02-05T03:36:09Z Show Answers