Printed Page 98(cont.)

4.5 Terms

Match each of the terms on the left with its definition on the right. Click on the term first and then click on the matching definition. As you match them correctly they will move to the bottom of the activity.

4.1 Central Tendency

Question

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central tendency (p. 78)
mean (p. 80)
statistic (p. 80)
parameter (p. 80)
median (p. 81)
mode (p. 83)
unimodal (p. 83)
bimodal (p. 83)
multimodal (p. 83)
The mode is the most common score of all the scores in a sample.
The mean is the arithmetic average of a group of scores. It is calculated by summing all the scores in a data set and then dividing this sum by the total number of scores.
A bimodal distribution has two modes, or most common scores.
Central tendency refers to the descriptive statistic that best represents the center of a data set, the particular value that all the other data seem to be gathering around.
A unimodal distribution has one mode, or most common score.
The median is the middle score of all the scores in a sample when the scores are arranged in ascending order. If there is no single middle score, the median is the mean of the two middle scores.
A statistic is a number based on a sample taken from a population; statistics are usually symbolized by Latin letters.
A multimodal distribution has more than two modes, or most common scores.
A parameter is a number based on the whole population; parameters are usually symbolized by Greek letters.

4.2 Measure of Variability

Question

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variability (p. 87)
range (p. 87)
variance (p. 88)
deviation from the mean (p. 88)
sum of squares (p. 89)
standard deviation (p. 90)
The range is a measure of variability calculated by subtracting the lowest score (the minimum) from the highest score (the maximum).
The sum of squares, symbolized as SS, is the sum of each score's squared deviation from the mean.
A deviation from the mean is the amount that a score in a sample differs from the mean of the sample; also called a deviation.
Variability is a numerical way of describing how much spread there is in a distribution.
Variance is the average of the squared deviations from the mean.
The standard deviation is the square root of the average of the squared deviations from the mean; it is the typical amount that each score varies, or deviates, from the mean.