Types of StatisticsDescriptive Inferential

MeansMediansModesPercentagesVariationDistributions

Draws conclusionsAssigns confidence to conclusionsAllows probability calculations

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)

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)

Three Kinds of Data

Nominal Ordinal IntervalCategorical No meanex: ● Marriage status ● GenderSounds like “NAME”

Natural orderingUnequal intervalsex: ● Rankings ● Survey dataSounds like “ORDER”

Extends ordinal dataEqual intervalsex: ● Temperature ● TimeSounds like what it is

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

Hurney JMBE 13:133-141 (2012)

Boone and Boone Journal of Extension 50:2TOT2 (April 2012)

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

Problem (Theory)

Question (Hypothesis)

Methods (treatment, control groups)

Intervention

Data (Triangulation)

Conclusions

Change practice

Adapted from D.C. Howell, Fundamental Statistics for the Behavioral Sciences (6th ed.) Wadsworth Cengage Learning (2008)

Type of Data

Differences

Two categories

One category

Interval (Quantitative)

Nominal or Ordinal(Qualitative)

Frequency, %, Goodness-of-fit,

Relationships

Type of Question

Frequency, %, Contingency table, Test

of Association,

Number of Groups

Number of Predictors

Multiple

One

Multiple Regression

Measurement

Ranks

Continuous

Spearman’s rS

Degree of Relationship

Form of Relationship

Primary Interest

Linear Regression

Pearson Correlation

Multiple

TwoRelation 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

1. Collect student demographic dataa) Want to discover if students between treatment

and control groups had the similar ethnic backgrounds

2. Collect test grades before and after interventiona) 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 learninga) 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

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.