1. Types of Statistics DescriptiveInferential Means Medians Modes Percentages Variation Distributions Draws conclusions Assigns confidence to conclusions Allows probability calculations

2. FIGURE 5. Student performance in (A) midsemester and (B) final exams across 2010 (n = 265) and 2011 (n = 264) offerings of MICR2000. Wang, Schembri and Hall JMBE 14:12-24 (2013)

3. FIGURE 6. Student Evaluation of Course and Teaching (SECaT) scores across 2010 and 2011 offerings of MICR2000. Students were invited to voluntarily respond to surveys regarding their evaluation of teaching within MICR2000 in 2010 (n = 108) and 2011 (n = 87) using a standardized University-Wide Student Evaluation of Course and Teaching (SECaT) survey instrument. Student responses corresponded to a 5 -point Likert scale and quantified as follows: 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree. Bars represent mean +/– standard error of the mean (SEM). *Denotes a statistically significant difference between student responses for 2010 and 2011 offerings of MICR2000, as determined by the Mann-Whitney U test (p < 0.05). Wang, Schembri and Hall JMBE 14:12-24 (2013)

4. Three Kinds of Data Nominal Ordinal Interval Categorical No mean ex: ● Marriage status ● Gender Sounds like “NAME” Natural ordering Unequal intervals ex: ● Rankings ● Survey data Sounds like “ORDER” Extends ordinal data Equal intervals ex: ● Temperature ● Time Sounds like what it is

5. Borgon et al., JMBE 13:35-46 (2013)

6. Hurney JMBE 13:133-141 (2012) Boone and Boone Journal of Extension 50:2TOT2 (April 2012)

7. Darland and Carmichael JMBE 13:125-132 (2012)

8. Problem (Theory) Question (Hypothesis) Methods (treatment, control groups) Intervention Data (Triangulation) Conclusions Change practice

9. Adapted from D.C. Howell, Fundamental Statistics for the Behavioral Sciences (6 th ed.) Wadsworth Cengage Learning (2008) Type of Data Differences Two categories One category Interval (Quantitative) Nominal or Ordinal (Qualitative) Relationships Type of Question Number of Groups Number of Predictors Multiple One Multiple Regression Measurement Ranks Continuous Spearman’s r S Degree of Relationship Form of Relationship Primary Interest Linear Regression Pearson Correlation Multiple Two Relation Between Groups Independent Dependent Independent samples t Mann- Whitney U Paired Samples t Wilcoxon Relation Between Groups Independent Dependent Number of Indep. Var. Repeated Measures ANOVA Friedman Multiple One One-Way ANOVA Kruskal- Wallis Factorial ANOVA

10. 1.Collect student demographic data a)Want to discover if students between treatment and control groups had the similar ethnic backgrounds 2.Collect test grades before and after intervention a)Want to see if your teaching intervention resulted in a significant difference in test scores between control and treated groups 3.Survey students on their own perceptions of learning a)Want to see if your teaching intervention resulted in a significant increase among responses to Likert-scale questions regarding student learning gains between control and treated groups

11. Graduate school level: You have categorized your students into three performance groups; novice, developing, and expert based on high school GPA and SAT data. You want to compare the performance of these groups on a critical thinking assessment before and after your teaching intervention.