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Experimental Psych Lab 1
Terms in this set (68)
statistics that allow you to summarize the properties of an entire distribution of scores with just a few numbers.
exploratory data analysis (EDA)
examining data for potentially important patterns and relationships, especially through the use of simple graphical techniques and numerical summaries.
in a data file, numbers used to stand for category values; for example, 0=male, 1=female.
organizing your data into a separate column for the scores from each treatment.
create one column for the participant IDs, a column for the treatment levels, and a column for each independent variable.
a graph on which data from groups of subjects are represented by bars of different heights tied to the value of the dependent variable for the group.
a graph on which data relating the variables are plotted as points connected by lines.
a relationship in which the value of the dependent variable varies as a function of the value of the independent variable.
a plot used to to display correlational data from two measures. each point represents the two scores provided by each subject, one for each measure, plotted against one another.
type of graph in which a circle is divided into segments. each segment represents the proportion or percentage of repsonses falling in a given category of the dependent variable.
a graph or table displaying a set of values or range of values of a variable, together with the frequency of each.
a graph depicting a frequency distribution in which the frequencies of class intervals are represented by adjacent bars along the scale of measurement.
a graphical display of a distribution of scores consisting of a column of values (the stems) representing the leftmost digit or digits of the scores and, aligned with each stem, a row of values representing the rightmost digit of each score having that particular stem value.
a frequency distribution in which most scores fall into categories above or below the middle category.
a specific type of frequency distribution in which most scores fall around the middle category. scores become less frequent as you mvoe from the middle category. also referred to as a bell-shaped curve.
statistics that are not strongly affected by the presence of outliers or skewness in the data.
measure of center
a single score, computed from a data set, that represents the general magnitude of the scores in the distribution.
the most frequent score in a distribution. the least informative measure of center.
a distribution with two modes.
the middle score in an ordered distribution.
the arithmetic average of the scores in a distribution. the most frequently reported measure of center.
measure of spread
a single score, computed from a data set, that represents the amount of variability of the scores in the distribution (i.e., how spread out they are).
the least informative measure of spread; the difference between the lowest and highest scores in a distribution.
a measure of spread in which an ordered distribution of scores is divided into four groups. the score separating the lower 25% is subtracted from the score separating the upper 25%. the resulting difference is divided by 2.
a measure of spread. the averaged square deviation from the mean.
the most frequently reported measure of spread. the square root of the variance.
a graphical display of the values of the five-number summary of a distribution.
measure of association
what you use to evaluate the direction and degree of relationship (correlation) between the scores in two distributions; includes Pearson r, point-biserial correlation, Spearman rank-order correlation or rho, and phi coefficient.
Pearson product-moment correlation coefficient or Pearson r
the most popular measure of correlation. indicates the magnitude and direction of a correlational relationship between variables.
a positive correlatio indicates this; as the values of the scores in one distribution increase, so do the values in the second.
a negative correlation indicates this; as the value of one score increases, the value of the second decreases.
a variation of the Pearson correlation used when one variable is measured on a dichotomous scale.
Spearman rank-order correlation or rho (p)
a measure of correlation used when variables are measured on at least an ordinal scale.
measure of correlation used when both variables are measured on a dichotomous scale.
statistical technique used to determine the straight line that best fits a set of data.
bivariate linear regression
a statistical technique for fitting a straight line to a set of data points representing the paired values of two variables.
least-squares regression line
straight line, fit to data, that minimizes the sum of the squared distances between each data point and the line.
value computed in a linear regression analysis that provides the slope of the least squares regression line.
standardized regression weight or beta weight (B)
standardized regression weight used to interpret the results of a linear regression analysis. can be interpreted as a partial correlation coefficient.
the difference between the values Y and Y-hat.
standard error of estimate
a measure of the accuracy of prediction in a linear regression analysis. it is a measure of the distance between the observed data points and the least squares regression line.
coefficient of determination
the square of the correlation coefficient; provides a measure of the amount of variance that two variables being tested share.
coefficient of nondetermination
statistic indicating the proportion of variance in one variable not accounted for by variation in a second variable.
a matrix giving the set of all possible bivariate correlations aomg three or more variables.
values of a variable in a set of data that lie far from the other values.
statistical procedures used to infer a characteristic of a population based on certain properties of a sample drawn from that population.
sampling distribution of the mean
when you can take every possible sample of n scores from the population; this distribution will tend to closely approzimate the normal distribution, even when the population of scores from which the samples were drawn is far from normal in shape.
standard error of the mean
an estimate of the amount of variability in expected sample means across a series of samples. it provides an estimate of the deviation between a sample mean and the underlying population mean.
degrees of freedom (df)
the number of scores that are free to vary in a distribution of a given size having a known mean.
estimates the value of a population from the characteristics of a sample.
makes no assumptions about the distribution of scores underlying your sample; used if your data do not meet the assumptions of a parametric test.
Type I error
deciding to reject the null hypothesis when, in fact, the null hypothesis is true. also referred to as an alpha error.
Type II error
deciding not to reject the null hypothesis when, in fact, the null hypothesis is false. also referred to as a beta error.
the probability of obtaining a difference at least as large as the one actually obtained, given that the difference occurred purely as a result of chance factors. by convention, the maximum acceptable level is .05 (5 chances in 100 or 1 chance in 20).
the particular level of alpha that you adopt.
if the difference between means yields an observed value of a statistic that meets or exceeds the critical value of your inferential statistic, you declare that difference to be this.
portion of the sampling distribution of a statistic within which observed values of a statistic are considered to be statistically significant. usually the 5% of cases found in the upper and/or lower tail(s) of the distribution.
an inferential statistic used to evaluate the reliability of a difference between two means. versions exist for between-subjects and within-subjects designs for evaluating a difference between a sample mean and a population mean.
t test for independent samples
a parametric inferential statistic used to compare the means of two independent, random samples in order to assess the probability that the two samples came from populations having the same mean.
unpooled version of t test for independent samples
computes an error term based on the standard error of the mean provided separately by each sample.
pooled version of t test for independent samples
computes an error term based on the two samples combined, under the assumption that both samples come from populations having the same variance.
t test for correlated samples
a parametric inferential statistic used to compare the means of two samples in a matched-pairs or a within-subjects design in order to assess the probability that the two samples came from populations having the same mean.
z test for the differences between two proportions
a parametric inferential statistic used to determine the probability that two independent, random samples came from populations having the same proportion of "successes" (e.g., persons favoring a particular candidate).
analysis of variance (ANOVA)
an inferential statistic used to evaluate data from experiments with more than two levels of an independent variable or data from multifactor experiments. versions are available for between-subjects and within-subjects designs.
the test statistic computed when using an analysis of variance. it is the ratio of the between-groups variance to within-groups variance.
in a statistical test, the probability, estimated from the data, that an observed difference in sample values arose through sampling error. must be less than or equal to the chosen alpha level for the difference to be statistically significant.
the alpha level for each of any multiple comparisons made among means.
the likelihood of making at least one Type I error across a number of comparisons.
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