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45 Cards in this Set

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 measures of central tendency also called measures of average mean median mode midrange measures of variation also called measures of dispersion range variance standard deviation measures of position used extensively in psychology and education, norms percentiles deciles quartiles parameters a characteristic or measurement obtained by using all data for a population statistic a characteristic or measure obtained using data values from a sample what is the general rounding rule? rounding should not be done until the final answer is calculated mean formula also known as the arithmic average add all values then divide by the number of values mean also known as the arithmic average add all values then divide by the number of values rounding rule for the mean the mean should be rounded to one more decimal place than occurs in the raw data median the midpoint of the data array data array ordered data 1 2 3 4 5 12 23 32 44 51 mode the value that occurs most often in a data set there can be one, none, or multiple modes a data set w/ multiple modes is bimodal the modal class the class with the largest frequency midrange formula a rough estimate of the middle (lowest value + highest value) / 2 midrange formula a rough estimate of the middle (lowest value + highest value) / 2 weighted mean formula used when values are not equally represented multiple each value by its corresponding weight, divide the sum of products by the sum of weights which varies less, mean, median or mode? mean varies the least of these Can a mean be computed for an open ended frequency distribution? no what are outliers? extremely high or low values that can affect the accuracy of the mean and the midrange can the median be used for open ended distributions? yes positively skewed distribution right skewed tail to the right symmetric distribution data is evenly distributed on both sides of the mean negatively skewed left skewed, tail to the left measurements for the spread of variability range variance standard deviation rounding rule for standard deviation final answer should be rounded to one more decimal place that the original data variance formula is the average of the squares of the distance each value is away from the mean subtract the mean from each value, square each difference, add all squared differences, divide the sum of squared differences by the population size the larger the variance or standard deviation,... the more variable the data the symbol for sample size is n the symbol for an individual value is x the symbol for range is R how do you find the standard deviation? take the square root of the variance the symbol for the population standard deviation is ó the symbol for the population standard deviation is ó the symbol for population mean is µ the symbol for sample mean is X (with a bar above it) the symbol for a sample standard deviation is s Chebyshev's theorem states that for any distribution___________________ of the data will fall within 2 standard deviations of the mean. 75% coefficient of variation formula standard deviation divided by the mean and expressed a percentage symbol for coefficient of variation CVar the empirical rule these are true with a normal distribution 1)appr. 68% of data values will fall within 1 standard deviation of the mean 2) 95% will fall within 2 3) 99.7% will fall within 3 z score formula also called standard score the number of standard deviations a number is from the mean (value-mean)/ standard deviation percentile formula [(number of values below x)+ .5] /total # of values, given as a percentage deciles divide the distribution into 10 groups find outliers Q1-[(Q3-Q1)*1.5] and Q3+[(Q3-Q1)*1.5] interquartile range Q3-Q1