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Perceived Conflict between Evolution and Religion Scale (PCoRE)

  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

z-scores or standard scores

  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

Worldview Assessment- An Example

  Graphic from  Pewresearch 2021 Pew Researchers have a great deal of experience in asking people questions. Formulating a good question for a survey is an important place to begin. However, another lesson from Pew is the additional data they gather. I noticed a large graphic illustrating how people in different groups answered one question. When conducting survey research it is critical to consider what we need to know about the people responding to a question or item to understand the meaning of their response. Consider Pew's survey item with two choices: "most things in society...      Can be pretty clearly divided into good and evil      Are too complicated to be divided into good and evil The graphic shows how different groups responded and allows for comparisons on the two ways to respond. Later, in the article, they compare political affiliations, which in the US means Republican and Democrat. This is worth studying as well. The article is worth reading to learn more ab

Belief in Good Luck (BIGL) review

  S cale name: Belief in Good Luck (BIGL) Scale overview: The scale presents 12-items, which are rated based on degree of agreement. The authors wanted to reliably assess irrational beliefs about luck and examine the beliefs in relationship to expectations of success. Early psychometric properties support the scale as a useful assessment of luck. Authors: Peter R. Darke and Jonathan L. Freedman   Response Type: 4-point agree-disagree scale Subscales: None Sample items b) Some people are consistently lucky, and others are unlucky. o) Luck is nothing more than random chance. (reverse scored) Reliability: Factor analysis yielded one factor. Items were selected from the original list based on factor loadings. Alpha   values were .85 in studies 1 and 3; .78 in study 2. Validity: The article includes correlation values with other measures. Total BIGL score was significantly positively correlated with the chance subscale of the Locus of Control scale. Availability:

Average Intelligence

  The concept of average intelligence is sometimes difficult to appreciate because the two words, average and intelligence, are sometimes not defined. Average   To psychologists and counselors who administer tests of intelligence, a person who scores at the 50th Percentile has average intelligence as defined by the number of correct answers to test tasks compared to others in their age group. Many tests set the middle score at 100 thus, 100 = average intelligence on many tests. All test scores vary from time to time so, a person may earn more or less points on another day. This fluctuation is estimated and can range for example by plus or minus 3-5 IQ points depending on the test and age group.  If you retake the test in a month or so, you may score better because of the “practice effect”—you’ve seen the items recently so you will probably do better. There is an average range so examiners will not focus on the obtained score but consider a broader range. For example, some may consider

Spiritual Abuse Questionnaire (SAQ) by Kathryn Hope Keller

  Scale name: Spiritual Abuse Questionnaire (SAQ) Scale overview: The  Spiritual Abuse Questionnaire (SAQ)  is a 17-item self-report questionnaire that uses a 4-point Likert Type response format to measure two dimensions of abuse: Power-based affective wounding and Conditionality. Author: Kathryn Hope Keller   Response Type: 4-point Likert type. The choices are: Strongly disagree, Disagree, Agree, Strongly agree. Subscales and Sample Items: There are two subscales. 1. Power-based Affective Wounding : “At times, I was scolded by my leader and made to feel ashamed and helpless” and “I now feel cynical about church/religious groups.”   2. Conditionality: “I believed I could be totally surrendered to God if I did everything perfectly according to the church/group’s instructions,” and “I believed God would punish me if I didn’t do what my church/group encouraged me to do.” Reliability: Alpha for the 17-item scale was .95 (Keller, 2016). The study sample was 271

Writing About Data in Psychology Papers and Reports

  Have you seen the data? The word data  is a plural noun and takes a plural verb. See the following two examples. Our data do not indicate why a discrepancy might exist, but the findings could be consistent with those of Kakhnovets (2011) who found that Extraversion was a factor for women but not men in seeking psychotherapy (Sutton et al., 2018, p.20). There are data suggesting that certain infants appear to actively suppress activation of the attachment system (i.e., have trouble seeking care). Cassidy, 2000, p. 116) We write: Data are not data is. Data were not data was. Data reveal not data reveals. Data show not data shows. If we wanted to write about one item from a data set, we could use the singular form, datum. One score in a set of scores is a datum. Datum is rarely used. Learn More about analyzing and writing about research in  Buy Creating Surveys  on GOOGLE BOOKS   AMAZON References Cassidy, J. (2000). Adult romantic attachments: A developmental perspective on indiv