Assessment, Statistics, and Research

 Students in many fields learn that relationships between variables may be described as a simple one-to-one correspondence or linear. We often see tables of correlations in journal articles and presentations. Unless otherwise stated, the correlations appear to assume a linear relationship exists. As one variable increases so does the other or as one variable increases, the other declines. But we also learn that some relationships are nonlinear such as the forgetting curve (remember Ebbinghaus) or the learning curve depicted as an S-shape. The classic learning curve illustrates the relationship between learning and experience and is often presented as an S-curve. At first, progress is slow—the curve of learning rises a little. Then, with experience, learning rises rapidly up to a point when it seems to level off at a person’s level of proficiency. This curve has many names such as progress curve, startup curve, and experience curve. However, we should follow the data rather than assume

 Frugal models or simple rules are prediction models using only a few variables. The approach is based on findings that in behavioural research many predictors are correlated with each other thus, a few variables with minimal to zero intercorrelations may be more powerful and simpler to understand and use. 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    

 Cross-validated correlation refers to validating relationships between studied variables in a new sample. 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    

In statistics, an effect size ( ES ) indicates the strength of the relationship between two variables. In psychological experiments, researchers are interested in the strength of the effect of the Independent Variable on the Dependent Variable. In psychotherapy studies, researchers may be interested in the effects of treatment on a measure of the dependent variable. A research questions may be framed: How effective is a set of 6 CBT sessions on the reduction of depression? Psychologists have often described effect sizes as small, medium, or large. Cohen's d Cohen's d is a measure of effect size between two groups. The mean of one group is subtracted from a second group and divided by the pooled standard deviation of the two groups. ES = (M1 - M2) / SD Effect Size  Label 0.2     Small 0.5     Medium 0.8     Large Pearson Correlation Coefficient ( r ) 0.1 to 0.3  Small 0.3 to 0.5  Medium 0.5 to 1.0   Large Converting Cohen's d to the correlation coefficient r =   d / √ d 2

  The Spearman-Brown formula estimates test score reliability of a full-length test when using a split-half method of reliability. The split-half method divides a test in two and calculate a correlation between the scores of the two halves. Longer tests are yield higher reliability values so the Spearman-Brown formula estimates the reliability value for the full test. Other names for the Spearman-Brown formula are Spearman-Brown Prophecy Formula, Spearman-Brown Correction. Learn more about test statistics in Buy Applied Statistics for Counselors   GOOGLE BOOKS   AMAZON 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  

  The term correlation can refer to a statistic and a type of research.  Understanding correlations is an important building block of many complex ideas in statistics and research methods. My focus in this post is on the common correlation statistic, also called the Pearson r . The Pearson r is a statistical value that tells the strength and direction of the relationship between two normally distributed variables measured on an interval or ratio scale . Researchers examine the two sets of values and calculate a summary statistic called a correlation coefficient . The longer name for a common correlation statistic is the Pearson Product Moment Correlation Coefficient but sometimes it is referred to as the Pearson r . The symbol for correlation is a lower case and italicized r .  In behavioural research, we normally round values to two decimal points. A moderately strong positive correlation example is r = .78.       Sometimes, the relationship between the two variables is negativ

  Cramer’s V . A correlation coefficient that may be used with nominal data. It is often included with chi-square test reports. Creating Surveys on AMAZON    or   GOOGLE  Worldwide Links to Connections Checkout My Website     www.suttong.com    See my Books    AMAZON             GOOGLE STORE   FOLLOW me on    FACEBOOK     Geoff W. Sutton          TWITTER    @Geoff.W.Sutton      PINTEREST    www.pinterest.com/GeoffWSutton   Read published articles:     Academia    Geoff W Sutton         ResearchGate    Geoffrey W Sutton  

Can you answer these questions that every counselor ought to know? Choose the BEST available answer. I'll post the answers below. 1. If the correlation between a test of intelligence and a test of achievement is usually between .88 and .92, how well can you use the intelligence test results to predict achievement test results? A. Very well B. Moderately well C. Not well at all D. None of the above 2. A personality test score was high on a scale of Extraversion. The validity of the Extraversion scale was reported as .52 to .57 compared to similar tests. How much confidence should the person have that their score is "valid?" A. A high degree B. A moderate degree C. A low degree D. None of the above 3. School counselors administered a questionnaire to 1,000 students. They calculated results for answers about four school improvements rated on a scale of 1 to 5. Most of the scores were in the range of 18 to 20. The counselors reported a mean rating o