Assessment, Statistics, and Research

Variance is a measure of the dispersion of values in a distribution of values.  In psychology and behavioral science statistics, the variance is typically a reference to the extent to which numerical values vary around the arithmetic mean of a data set. Theoretically, the values vary around a population mean but in most cases, researchers work with samples. In statistics, write sigma squared for the population variance σ 2 Write final form sigma squared for the sample variance  ς2 In reports, write VAR for variance. How it works If we have a set of different numerical values such as scores on a test we can calculate a mean, which is the average of all the scores divided by the number of scores. The difference of one score from the mean is a deviation score. X is a score and the Greek letter mu μ is the symbol for the population mean. In a sample, which is what we normally have in psychology, we subtract a score X from the sample mean M . Thus, X - M = the deviation score.  If a perso

  Factor analysis (FA)  is a statistical method of reducing a large set of data to a smaller set by identifying patterns in the data that have common characteristics. Factor analysis is sometimes called data reduction or dimension reduction. The original numerical values in the data set are observed variables (also called manifest variables)  such as the items in a large survey or test. Factor analysis may find patterns characterized by a shared statistical relationship representing a factor, which is also called a dimension . A researcher examines the content of the items linked to this factor and chooses a factor label such as verbal skills for related items on an intelligence test. The factors may be treated as variables in additional research. These are secondary variables. Because they are created from the observed variables, they are considered latent variables. For example, if 5 items on a personality test are associated with one factor labeled "agreeableness" then agr

  Scale name: Perceived Conflict between Evolution and Religion (PCoRE) Scale overview: Authors: M. Elizabeth Barnes, K. Supriya, Yi Zheng, Julie A. Roberts, and Sara E. Brownell Response Type: Participants rate each item on a 5-point Likert-type scale from strongly disagree to strongly agree.   Subscales with a sample item: There are four subscales as follows:   1. Perceived conflict between evolution and belief in God My belief in God makes it harder to believe that all of life on Earth evolved from ancient microscopic life.   2 . Perceived conflict between evolution and religious teachings The teachings of my religion contradict that all of life on Earth evolved from ancient microscopic life.   3 . Perceived conflict with evolution among religious community My religious community does not believe that all of life on Earth evolved from ancient microscopic life.   4. Perceived conflict between evolution and religious beliefs My personal religious belief

  A z -score tells you the distance of the score from the arithmetic mean of a set of scores that are normally distributed. The z -score represents standard deviation units thus, a z -score of 1 means it is one standard deviation above the mean of the set of scores. A z -score of minus one (-1) means the score is one standard deviation below the mean of the set of scores. The z -scores are often plotted along the x -axis of  a normal distribution, which is sometimes called the bell curve. Use lower case italics when reporting z -scores in APA style. The upper case Z is a different score. You can calculate a  z -score by subtracting a raw score from the mean and dividing by the standard deviation of the set of scores. Example: A raw score on a test = 60. If the mean = 50 and the standard deviation = 10 then (60-50) = 10 and 10 divided by 10 = 1.0. The z score is 1.0, it is one standard deviation above the mean. Most z - scores fall between -3.0 and +3.0 but it is possible to have scor