Assessment, Statistics, and Research

  A post hoc test is a statistical test used to determine if a pair of values are significantly different from each other after the primary analysis has been completed. The term post hoc is a Latin phrase meaning after the event. A common use of post hoc tests is the comparison of group means after an F -test in an ANOVA has revealed significant differences among the groups. The reason to test for differences after an overall test like ANOVA is to reduce the risk of finding a significant difference by chance. That is, if researchers perform a large number of tests on a sample, they may find one or more tests significant by chance. There are many post hoc tests. Following are some examples of tests that compare the means of two groups. Bonferroni Test This is a popular test. By dividing the significance level by the number of comparisons, the risk of finding a significant difference by chance is reduced. This procedure is called the Bonferroni Correction. Tukey's Honest Significant

  MANCOVA (Multivariate Analysis of Covariance). A statistical procedure for analyzing results when there are one or more independent variables , two or more dependent variables , and one or more covariates . Basic components of MANCOVA Independent or grouping Variable = 1 or more Dependent or criterion Variable = 2 or more Covariates = 1 or more Overall tests are used to determine significant effects or differences among the grouping variables. An F test indicates significance overall and for specific effects or relationships. A commonly reported measure of effect size is eta squared. A p value reveals the probability of a significant relationship-- one that is not due to chance factors. Applied Statistics Concepts for Counselors on  AMAZON  or  GOOGLE Creating Surveys on AMAZON    or   GOOGLE  Worldwide Links to Connections   Checkout My Website     www.suttong.com    See my Books      AMAZON             GOOGLE STORE   JOIN me on      FACEBOOK     Geoff W. Sutton          TWITTER  

  ANCOVA ANCOVA is a procedure like ANOVA except researchers can study the effects of one or more independent variables on a dependent variable after adjusting for other variables, called covariates , which were not a primary focus of the study. The letter C in ANCOVA stands for covariate . There can be several covariates in a study. In testing for differences among groups experiencing different leadership styles, we could study the effects on employee satisfaction after adjusting for a covariate of years of employment. A key word in ANCOVA studies is adjusting . Analysts adjust the scores based on information about the covariate before testing for significant differences. Basic features of an ANCOVA: Independent or grouping Variable = 1 or more Dependent or criterion Variable = 1 Covariates = 1 or more An  F  test indicates significance overall and for specific effects or relationships. A commonly reported measure of effect size is eta squared. A  p  value reveals the probabilit

There are several types of ANOVA procedures. The term ANOVA refers to Analysis of Variance . Variance is a statistical term we will review later. Variance refers to differences, so the ANOVA procedures examine differences in scores among groups of people who complete a survey, a test, or produce a scorable response. For example, an ANOVA can be used to assess the effects of three temperatures on math. The Independent Variable is temperature varies three ways (75, 85, 95 degrees F). The dependent variable is math. The dependent measure of math is a math test. When there is only one independent variable (IV), the ANOVA is called a one-way ANOVA. If there are two IVs the ANOVA is a two-way ANOVA, and so forth. It is rare to go beyond a four-way because the interpretation of interactions is complicated. The ANOVA procedure is usually reported with an F value. The larger the F value, the more likely it is that the differences the researchers found are not due to chance. There may be s

  MANOVA MANOVA is the abbreviation for Multivariate Analysis of Variance . The M stands for multivariate and refers to the presence of more than one dependent variable. A MANOVA may have one or more independent variables and two or more dependent variables. For example, we could examine the effects of different presenters and different forgiveness programs on forgiveness and compassion. Studies with three to four independent variables and three to four dependent variables can be difficult to interpret because many interactions are possible. Independent or grouping Variable = 1 or more Dependent or criterion Variable = 2 or more Overall tests are used to determine significant effects or differences among the grouping variables. An  F  test indicates significance overall and for specific effects or relationships. A commonly reported measure of effect size is eta squared. A  p  value reveals the probability of a significant relationship-- one that is not due to chance factors. Read m

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