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Confounding variables in behavioral research

  A Confounding variable  is a variable that produces unexpected changes in the dependent variable and therefore interferes with interpreting the capacity of an independent variable   to produce or explain changes in a dependent variable . Example : During a study of anxiety that includes measures of anxiety and stress, some participants watch a documentary about the treatment of anxiety and some do not. Documentary-watching may confound the results if watching the program influenced the scores on the measures of anxiety and stress. Similarly, some participants may be exposed to a source of stress in their environment but others are not, which could interfere with interpreting the results. Learn More about research methods and variables in Creating Surveys on  AMAZON  or  GOOGLE Please check out my website     www.suttong.com    and see my books on    AMAZON         or   GOOGLE STORE Also, consider connecting with me on     FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.

Concurrent validity in testing

  Concurrent validity is a  method of test score validity based on the correlation of two sets of scores obtained at the same time. Example: A clinician creates a test of anger and hands the test to patients for completion. High scores represent high levels of anger. A different clinician rates the level of anger in the same patients based on interviews and rates the level on a scale of 1-10. Each patient has two sets of anger scores. A researcher can calculate the correlation between the test and the ratings. If the correlation is moderately high and not likely due to chance, then there is evidence for concurrent validity when using the new test under similar situations. Applied Statistics Concepts for Counselors on    AMAZON  or   GOOGLE Please check out my website     www.suttong.com    and see my books on    AMAZON        or   GOOGLE STORE Also, consider connecting with me on    FACEBOOK     Geoff W. Sutton          TWITTER    @Geoff.W.Sutton       You can read many published arti

Categorical or Grouping variable in Behavioral Research

  Categorical variables are those variables having two or more groups or levels such as sex, ethnicity, and religious group.  They may be called independent variables even though they are not true independent variables under experimental control. Categorical variables, also called grouping variables,  can be created from continuous variables . For example, researchers often obtain the age of their study participants. Age is a continuous variable but sometimes, researchers group ages together and compare how people of different age groups answer questions on a survey. Learn More in Creating Surveys on  AMAZON  or  GOOGLE Please check out my website     www.suttong.com    and see my books on    AMAZON         or   GOOGLE STORE Also, consider connecting with me on     FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.W.Sutton     You can read many published articles at no charge:   Academia    Geoff W Sutton       ResearchGate    Geoffrey W Sutton  

Alpha in Research & Statistics

  In research, alpha is  the probability of rejecting a true null hypothesis.  In testing, alpha also refers to a measure of internal consistency—see Cronbach’s coefficient alpha. Alpha waves are brain waves that can be measured on an electroencephalogram (EEG). Alpha waves are associated with daydreaming, meditating, and mindfulness. Applied Statistics Concepts for Counselors on    AMAZON  or   GOOGLE Please check out my website     www.suttong.com    and see my books on    AMAZON        or  GOOGLE STORE Also, consider connecting with me on    FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.W.Sutton     You can read many published articles at no charge:   Academia    Geoff W Sutton      ResearchGate    Geoffrey W Sutton   Please check out my website     www.suttong.com    and see my books on    AMAZON        or  GOOGLE STORE Also, consider connecting with me on    FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.W.Sutton     You can read many published artic

Kurtosis

 Kurtosis is a statistical concept. The value indicates whether a distribution is similar to the normal curve or different from the normal curve. Compared to the normal curve, kurtotic distributions of data appear either peaked in the middle or flat. In a normal distribution, the value of kurtosis = 0. The peaked distribution has a positive value. It's called leptokurtic (think leap). The flatter distribution has a negative value. It's called platykurtic (think of the animal, Platypus). There are different formulas for calculating kurtosis. In Excel, the function for kurtosis can be found under Formulas, More Functions. In the drop down list, choose KURT. Please check out my website     www.suttong.com    and see my books on    AMAZON         or   GOOGLE STORE Also, consider connecting with me on     FACEBOOK     Geoff W. Sutton         TWITTER    @Geoff.W.Sutton     You can read many published articles at no charge:   Academia    Geoff W Sutton       ResearchGate   

Santa Clara Strength of Religious Faith Questionnaire

  Scale name: Santa Clara Strength of Religious Faith Questionnaire,   SCSRF, SCSRFQ Short form as an “Abbreviated” form, ASCSRFQ Scale overview A short easy to score measure of the strength of a person’s religious or spiritual faith. It is a available in 10-item and 5-item Likert-type scale formats. Author(s) Thomas G. Plante and Marcus T. Boccaccini introduced the 10-item version in 1997. Items: 10 and 5 for the short form   Response Type: 4-point self-report rating scale Subscales: None   Sample items 2. I pray daily. 10. My faith impacts many of my decisions. The short form uses the following 5-items: 2,4,5,8 (Plante et al., 2002). Statistics In the 1997 article, psychology students M = 26.39, SD   = 8.55, R = 33, Mdn = 26. A summary of previous studies using the 10-item version (Plante, 2010) found M = 26-33 in college samples with SD   = 6 to 8. There were no significant differences between the means of men ( M = 17.48, SD   = 2.52) and

Coefficient Alpha or Cronbach's Alpha

  Coefficient Alpha (also called "alpha") is a statistical value indicating the degree of internal consistency of items in a multiple-item scale like survey items or Likert-type scales. Internal consistency is one measure of reliability for scores from scales, measures, and survey items. The alpha statistic was developed by Lee Cronbach in 1951 thus it is also called Cronbach's alpha . In research reports, you may just see the Greek lower case letter alpha,  α. The procedure to calculate alpha can be found in SPSS under Analyze > Scale > Reliabilty. For research purposes, scales with alpha levels equal to or above alpha = .70 are acceptable. The best scales have values of alpha = .9 or higher. The alpha method works best to evaluate unidimensional measures. If there are two or more dimensions in a set of items, the alpha value will be lower so, when alpha values are low, consider which item or items do not support the primary dimension. Cite this Post Sutton, G.W.