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| statistical procedures used to summarize and simplify data |
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| consists of techniques that allow us to study samples and then make generalizations about a population |
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| consists of separate indivisible categories (no values can exist between two neighboring categories) |
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| there are an infinite number of possible values that fall between any two observed values; divisible into an infinite number of parts |
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| the boundaries of intervals for scores that are represented on a continuous line; real limit separating two values is located directly in the middle |
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| a characteristic or condition that changes or has different values for different individuals |
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| consists of a set of categories that have different names and measurements label and categorize observations, but do not make any quantitative distinctions between observations |
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| consists of a set of categories that are organized in an ordered sequence and measurements rank observations in terms of size or magnitude |
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| consists of ordered categories that are all intervals of exactly the same size and equal distances on the scale reflect different magnitudes |
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| an interval scale with the additional feature of an absolute zero point and ratios of numbers reflect ratios of magnitude |
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| an organized tabulation of the number of individuals located in each category on the scale of measurement |
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| grouped frequency distribution |
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| groups the scores into around ten intervals |
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| like a bar graph but displays the real limits of values |
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| leaves spaces between adjacent bars |
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| places a dot for the frequency of each score and connects them with a line |
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| places all but the last digit on the left and puts the last digit on the right; provides a view of the frequency and gives you the scores |
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| are symmetrical with the most scores right in the middle |
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| positive and negative skew |
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positive skew: to the left
negative skew: to the right |
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| a measure of the "peakedness" of the distribution; higher kurtosis means that more of the variance is the result of extreme scores; normal distribution has kurtosis of zero |
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| the sum of the scores divided by the number of scores |
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| What happens to the mean when you add or subtract a constant from each score? |
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| the same constant is added or subtracted from the mean |
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| What happens to the mean when you multiply or divide every score by a constant? |
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| the mean changes in the same way |
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| the score that divides the distribution in half; equivalent to the 50th percentile |
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| the score or category that has the greatest frequency; can be bimodal or multimodal |
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| Which measure of central tendency would you use for extreme or skewed distributions? |
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| Which measure of central tendency would you use for distributions with undetermined values? |
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| Which measure of central tendency would you use for an open ended (no upper of lower limit for one of the categories) distribution? |
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| What is the preferred measure of central tendency for ordinal data? |
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| Which measure of central tendency is best for data from a nominal scale? |
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| Which measure of central tendency is best for discrete variables? |
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| Which measure of central tendency describes the shape of the distribution? |
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| provides a quantitative measure of the degree to which scores in a distribution are spread out or clustered together |
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| the difference between the upper real limit of the largest (maximum) X value and the lower real limit of the smallest (minimum) X value |
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| the range covered by the middle 50% of the distribution |
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| half of the interquartile range |
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| mean squared deviation (the mean of the squared deviation scores |
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| the square root of the variance |
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| Will adding a constant to each score change the distribution? |
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| What will multiplying each score by a constant do to the standard deviation? |
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| it will cause it to be multiplied by the same constant |
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| the distribution of z-scores that a distribution can be transformed into |
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| a score when it is identified by its percentile rank |
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| the percentage of individuals int he distribution with scores at or below the particular value |
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| a fraction or a proportion of all the possible outcomes |
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| sampling distribution of means |
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| the collection of sample means for all the possible ransom sample of a particular size (n) that can be obtained from a population |
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| for any population with mean and standard deviation, the distribution of sample means for sample means for sample size n will have a standard deviation of (u) and a standard deviation of (o/n^1/2) and will approach a normal distribution as n approaches infinity |
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| states that there is no difference between sample mean and population mean |
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| states that there is a significant difference between the sample and population means |
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| indicates that the sample data are converted into a single, specific statistic that is used to test the hypothesis |
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| level of significance (alpha) |
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| probability of a Type I error; a probability value that is used to define the very unlikely sample outcomes if the null hypothesis is true |
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| indicates that the sample data are converted into a single, specific statistic that is used to test the hypothesis |
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| occurs when a researcher fails to reject a null hypothesis that is really false; means that the hypotheses test has failed to detect a real treatment effect |
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| composed of extreme sample values that are very unlikely to by obtained if the null hypothesis is true; boundaries determined by alpha level |
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| a measure of the strength of the relationship between two variables in a population or sample-based estimate of that quantity |
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| the probability that the test will correctly reject a false hypothesis (probability that the test will identify a treatment effect if one really exists) |
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| used to test hypotheses about an unknown population mean when the standard deviation is unknown; formula has the same structure as the z-score formula, except that the t statistic uses the estimated standard error in the denominator |
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| describe the number of scores in a sample that are independent and free to vary |
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| the variable that is manipulated by the researcher |
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| the variable that is observed in order to asses the effect of the treatment |
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| measures the proportion to which a mathematical model account for the variation of the given data set |
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| you use a single number as your estimate of an unknown quantity |
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| when an interval estimate is accompanied by a specific level of confidence (or probability) |
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| subjects are randomly assigned to treatment conditions (levels of the independent variable); excellent for showing a cause/effect relationship |
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| measurement in the treatment level is determined by conditions beyond the control of the experimenter (subjects fall in pre-existing groups) |
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| two variables are observed to determine whether there is a relationship between them |
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| measures the degree and direction of linear relationship between two variables |
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| identifies a measurement procedure (a set of operations) for measuring an external behavior and uses the resulting measurements as a definition and a measurement of a hypothetical construct |
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| What are the two components of an operational definition? |
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1) describes a set of operations for measuring a construct
2) defines the construct in terms of the resulting measurements |
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| any method of sampling that utilizes some form of random selection (have some process that assures different units in population have an equal chance of being selected) |
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| subjects are not randomly selected |
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| an extraneous variable that correlates (positively or negatively) with both the IV and DV; control these factors to avoid a type I error |
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| bias towards a result expected by the experimenter |
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| the participant believes they know the purpose of the experiment and perform in a way that will support or discredit the experiment |
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| What are the advantages of the within-subjects design? |
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| same group of subjects serves in more than one treatment;increases the power; reduces the error variance associated with individual differences |
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| What is the disadvantage of the within-subjects design? |
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| What are the two carryover effects? |
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| What is a between-subjects design? |
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| use different subjects for each treatment condition |
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| What are the advantages of the between-subjects design? |
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| sometimes the within-subjects design is improbable to use; no carryover effects |
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| What are the disadvantages of the between-subjects design? |
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| scale of experiment can make it improbable to get the number of subjects necessary; individual differences can skew data; assignment bias (fail to assign random groups); environmental factors; generalization (cannot extrapolate the results to encompass wider groups) |
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| What is the difference between a positive and negative correlation? |
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| In a positive correlation the two variables tend to move in the same direction, while in a negative correlation the two variables tend to move in opposite directions |
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| the statistical technique for finding the best-fitting straight line for a set of data |
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| What is a multiple regression used for? |
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| it is used to asses which of the possible independent variables is mainly responsible for the change in the dependent variable |
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| tests that concern parameters and require assumptions about parameters (t-test, anova, etc) |
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| do not have homogeneity of variance or a normal distribution (e.g. Chi-square test) |
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| uses sample data to test hypotheses about the shape or proportions of a population distribution; determines how well the obtained sample proportions fit the population proportions specified by the null hypothesis |
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| encloses the data in a correlation graph; shows the shape and trend in the distribution |
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