Exam 1

• Magnitude: the instance of an attribute being measured can be judged greater than, less than, or equal to another.
• Equal Intervals: scale units of measurement are equal across the scale.
• Absolute Zero Point: a value indicating that nothing of the attribute being measured exists.
• Ratio Scale: possesses magnitude, equal intervals, and an absolute zero point.
• Interval Scale: possesses magnitude and equal intervals, but no absolute zero point.
• Ordinal Scale: reflects only magnitude. Does not possess equal intervals or absolute zero points.
• Nominal Scale: classification of items into mutually exclusive groups that do not bear any magnitude relationships to one another.
• Continuous variable: can theoretically assume an infinite number of values between any 2 points on the measurement scale.
• Discrete variable: can only assume a countable number of values between 2 points.
• Central Tendency: a point on the scale corresponding to a typical, representative, or central score.
• Variability: the extent to which scores in a distribution deviate from their central tendency.
• Skewness: refers to an asymmetric distribution in which the scores are bunched on one side and trail out on the other.
• Kurtosis: "curvedness" or "peakedness" of the distribution graph.
• Leptokurtic: when the kurtosis is peaked.
• Platykurtic: when the kurtosis is flatter.
• Mean: the average of the scores in the distribution.
• Median: the point on the measurement scale that divides the distribution into two parts such that equal numbers of scores or cases lie above and below that point.
• Mode: most frequently occurring score value.
• Bimodal: a distribution with 2 modes.
• Multimodal: a distribution with more than 2 modes.
• Range: the largest score minus the smallest score in the distribution.
• Variance: reflects the degree of variability in a group of scores.
• Standard Deviation: the positive square root of the variance.
• The advantage of the standard deviation over the variance is that s expresses variability in the original units of measure.
• Standard scores: created to characterize the relative position of scores.
• Frequency: how often something occurs.
• Frequency Distribution: indicated the number of cases observed at each score value or within each interval of score values in a group of scores.
• Relative Frequency Distribution: distribution that indicates the proportion of the total number of scores occurring at each score value.
• Cumulative Frequency Distribution: the entry for a score value or interval is the sum of the frequencies for that value/interval plus the frequencies of all lower score values.
• Cumulative Relative Frequency Distribution: the entry for any score value or class interval expresses that value/interval’s cumulative frequency as a proportion of the total number of cases.