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the average, calculated by dividing the
sum of several values by the number of values


the middle value of a group of values, found by arranging all the observations from lowest value to highest value and picking the middle one


a measure of the spread of values within a group; calculated by dividing the sum of each values variation (the difference between the value and the mean) squared by the count (total number of values) minus one


the most frequent value in a group of values

standard deviation

the average difference of each value in a group from the mean value; calculated by taking the square root of the variance

confidence interval

the level of certainty that the true score falls within a specific range. The smaller the range the less the certainty.

interquartile range

the difference between the scores (or estimated scores) at the 75th percentile and the 25th percentile. Used more than the range because it eliminates extreme scores.

skewed distribution

not normal, or not bell curved, Any distribution of values which is not normal, that is not symmetrical along the x-axis

normal distribution

symmetrical distribution of values (mean=median) expected when a sample is taken from a large population; forms a bell-shaped curve called the normal curve

standard error of the mean

a measure of precision, the index that tells us how much a particular mean is likely to vary from one sample to another when all samples are drawn from the same population; the standard deviation of the sampling distribution of the mean

null hypothesis

hypothesis that states there is no difference between two or more sets of data.

type 1 error

incorrectly rejecting the null hypothesis, a false positive; AKA "A error"

type 2 error

incorrectly accepting the null hypothesis, a false negative; AKA "B error"

p value

the probability that the differences between two groups of values are due to chance; i.e. the probability that a null hypothesis has been mistakenly rejected, the probability that you have a false positive


generally accepted characteristic of significant results, meaning the probability that the null hypothesis was mistakenly rejected is less than 5%, i.e. the probability that the null hypothesis is false is 95%

p >.05

the probability that randomly generated results would resemble the observed results is more than 5%, rendering the results not significant

the t test

assesses whether the means of two groups (eg. control group and experimental group) are statistically different from each other, assumes that each group is sampled from different populations and that the distributions of the variable of interest are normal;

linear regression

defines a line of best fit for correlational data that can be used as a prediction equation


a measure of the extent to which two factors vary together (covary); a reciprocal relation between two or more things; CORRELATION DOES NOT ENTAIL CAUSATION, but it does suggest causation

chi squared test

compares the observed data (o) with the results that would be expected by chance (e), and tests the likelihood that the differences observed and expected are accidental, X=(o-e)^2/e; the higher X the more significant the results

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