Psyc 2260 Test 1

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STATISTICS

Back 1

branch of mathematics that focuses on the organization, analysis and interpretation of a group of numbers.

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DESCRIPTIVE STATISTICS

Back 2

Procedures for summarizing a group of scores or other-wise making them more comprehensible.

Front 3

INFERENTIAL STATISTICS

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Procedures for drawing conclusions based on the scores collected in a research study but going beyond them.

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VARIABLE

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Characteristics that can have different values.

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VALUES

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Possible number or category that a score can have.

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SCORE

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Particular person's value on a variable.

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NUMERIC VALUE AKA QUANTITIVE VARIABLE

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Variable whose values are numbers (as opposed to a nominal variable).

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EQUAL-INTERVAL VARIABLE

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Variable in which the numbers stand for approximately equal amounts of what is being measured.

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RATIO SCALE

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An equal-interval variable is measured on a ratio scale if it has an absolute zero point, meaning that the value of zero on the variable indicates a complete absence of the variable.

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DISCRETE VARIABLE

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Variable that has specific values and that cannot have values between these specific values.

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CONTINUOUS VARIABLE

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Variable for which, in theory, there are an infinite number of values between any two values.

Front 12

RANK-ORDER VARIABLE AKA ORDINAL VALUE

Back 12

Numeric variable in which the values are ranks, such as class standing or place finished in a race.

Front 13

NOMINAL VARIABLE AKA CATEGORICAL VARIABLE

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Variable with values that are categories.

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LEVELS OF MEASUREMENT

Back 14

Types of underlying numerical information provided by a measure, such as equal-interval, rank-order and nominal.

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FREQUENCY TABLE

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Listing of number of individuals having each of the different values for a specific variable.

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INTERVAL

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Range of values in a grouped frequency table that are grouped together.

Front 17

GROUPED FREQUENCY TABLE

Back 17

Frequency table in which the number of individuals is given for each interval of values.

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HISTOGRAM

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Barlike graph of a frequency distribution in which the values are plotted along the horizontal axis and the height of each bar is the frequency of that value; the bars are usually placed next to each other without spaces, giving the appearance of a city sky line.

Front 19

FREQUENCY DISTRIBUTION

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Pattern of frequencies over the various values

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UNIMODAL DISTRIBUTION

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Frequency distribution with one value clearly having a larger frequency than any other.

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BIMODAL DISTRIBUTION

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Frequency distribution with 2 approximately equal frequencies, each clearly larger than any of the others.

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MULTIMODAL DISTRIBUTION

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Frequency distribution with 2 or more high frequencies separated by a lower frequency.

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RECTANGULAR DISTRIBUTION

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Frequency distribution in which all values have approximately the same frequency.

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SYMMETRICAL DISTRIBUTION

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Distribution in which the pattern of frequencies on the left and right side are mirror images.

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SKEWED DISTRIBUTION

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Distribution in which the scores pile up on one side of the middle and are spread out on the other side.

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FLOOR EFFECT

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Situation in which many scores pile up at the low end of a distribution because it is not possible to have any lower score.

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CEILING EFFECT

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Situation in which many scores pile up at the high end of a distribution because it is not possible to have a higher score.

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NORMAL CURVE

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specific, mathematically defined, bell-shaped frequency distribution that is symmetrical and unimodal.

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KURTOSIS

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Extent to which a frequency distribution deviates from a normal curve in terms of whether its curve in the middle is more peaked or flat than the normal curve.

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CENTRAL TENDENCY

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Typical or most representative value of group of scores.

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MEAN

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Arithmetic average of a group of scores; sum of the scores divided by the number of scores

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MODE

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The value with the greatest frequency in a distribution.

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MEDIAN

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Middle score when all the scores in a distribution are arranged from lowest to highest,

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OUTLIER

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Score with an extreme value in relation to the other scores in a distribution

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VARIANCE

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Measure of how spread out a set of scores are; average of the squared deviations from the mean,.

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Deviation Score

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Score minus mean

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Squared deviation score

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Square of the difference between a score and the mean.

Front 38

Sum of squared deviations

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Total of all the scores of each score's squared difference from the mean

Front 39

Standard Deviation

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Square root of the average of the squared deviations from the mean

Front 40

Computational Formula

Back 40

Equation mathematically equivalent to the definitional formula.

Front 41

Definitional Formula

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Equation for a statistical procedure directly showing the meaning of the procedure.

Front 42

Z Scores

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Number of standard deviations that a score is above (or below, if its negative) the mean of its distribution; It is thus an ordinary score transformed so that it better describes the score's location in a distribution.

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Raw Score

Back 43

Ordinary score (or any number in a distribution before it has been made into a Z score or otherwise transformed.

Front 44

Normal Curve Table

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Table showing percentages of scores associated with the normal curve

Front 45

Expected Relative Frequency

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Number of successful outcomes divided by the number of total outcomes you would expect to get if you repeated an experiment a large number of times

Front 46

Long-Run-Relative-Frequency Interpretation of probability

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Understanding of probability as the proportion of a particular outcome that yoyo would get if the experiment were repeated many times.

Front 47

Subjective Interpretation of probability

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Way of understanding probability as the degree of one's certainty that a particular outcome will occur.

Front 48

Hypothesis Testing

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Procedure for deciding whether the outcome of a study support a particular theory.

Front 49

hypothesis

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Prediction, based on informal observation, previous research or theory that is tested in a research study.

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Theory

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Set of principles that attempt to explain one or more facts, relationships or events.

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Research Hypothesis

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Statement in hypothesis testing about the predicted relation between populations

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Null Hypothesis

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Statement about a relation between populations that is the opposite of the research hypothesis or about a relation between populations that there is no difference.

Front 53

Comparison Distribution

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A distribution used in hypothesis testing. It represents the population situation if the null-hypothesis is true. It is the distribution to which you compare the score based on your sample results

Front 54

Cutoff Sample Score AKA Critical Value

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Point in the hypothesis testing, on the comparison distribution at which, if reached or succeeded by the sample score, you reject the null hypothesis.

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Statistically significant

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Conclusion that the results of a study would be unlikely if in fact the sample studied represents a population that is no different from the population in general; an output in which the null hypothesis is rejected.

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Directional Hypothesis

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Research hypothesis predicting a particular direction of difference between populations- for example, a prediction that the population like the sample studied has a higher mean than the population in general.

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One-Tailed test

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Hypothesis testing procedure for a directional hypothesis; situation in which the region of the comparison distribution in which the null-hypothesis would be rejected is all on one side of the distribution

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Non-Directional hypothesis

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Research Hypothesis that does not predict a particular direction of difference between the population like the sample studied and the population in general.

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Two-Tailed Test

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Hypothesis-testing procedure for a non-directional hypothesis; the situation in which the region of the comparison distribution in which the null hypothesis would be rejected is divided between the 2 sides if the distribution

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Distribution of means

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Distribution of means of samples of a given size of a population

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Confidence Interval

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Roughly speaking, the range of scores that is likely to include the true population mean; more precisely, the range of possible population means from which it is not highly unlikely that you could have obtained your sample mean.

Front 62

Confidence limit

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Upper or lower value of confidence intervaL