Published on 28 Mar 2018

School

Department

Course

Professor

Lecture 4

Symmetric Distribution

• Perfect symmetric bell curves

• Extreme scores in both tails have a canceling effect on the mean, located at the center of

the distribution

o Mean = median = mode

• Positively skewed distribution

o Outlier scores on the high side of the distribution pull the mean toward the extreme

values

o Mode ignores the outliers, picks the most common score

o Median also ignores the outliers, picks the middle score

o Mean accounts for the outliers - everyone in the sample has an impact on the mean

• Negatively skewed distribution

o Outlier scores on the low side of the score range pull the mean down toward the

extreme

Comparing distributions

• Psychology research studies examine whether systematic differences exist among two or

more groups

o Examining and comparing means if a common way to evaluate group differences

• how dispersed people are in the variable on the score scale

• Conveys the idea that two or more things differ

• Variability is an important concept in statistics

o Refers to the degree of similarity/dissimilarity to a set of scores

Ex) using the center of town to create data in numbers

• Average distances, find the mean

Deviation Scores - d for distance

• Measure of statistical distance (variability) between an individual score and center of

distribution

• Score = mean + deviation

• Score - mean = deviation

• Deviation = individual score - mean

o Mean is the center of town (center of distribution)

o Subtract score from mean, we are finding how far from the center they are

o Deviation is like the distance on the map

Deviations always sum to zero

• When computed relative to the mean

• To compute the average deviation (distance)

o Ignore the negatives and add them all up, divide by the number of scores.

Standard Deviation

• The average difference (distance) between a set of scores and the mean

• Uses squaring to eliminate negative errors but is conceptually similar to averaging

absolute deviations

o Standard = typical

• For population - greek symbol sigma

find more resources at oneclass.com

find more resources at oneclass.com

## Document Summary

Ex) using the center of town to create data in numbers: average distances, find the mean. Deviations always sum to zero: when computed relative to the mean, to compute the average deviation (distance) Ignore the negatives and add them all up, divide by the number of scores. To compute: deviation score is another name for error, (x-mu, score for one participant - population mean, distance between a score and the mean (center of distribution, square deviation scores, (x-mu)^2, deviation scores must sum to zero. The variance is the average squared deviation: to unsquare - you just square root. Ex) typical respondent is +/- 6. 87 points from the mean: average of the distances from the mean. A problem with the population formula: computes error relative to the true population mean, we will never know the true population mean, sample mean is not the same as the actual population mean.