STATISTICAL ANALYSIS 101
STATISTICAL ANALYSIS 101
Dr. Marla Kniewel Nebraska Methodist College
OBJECTIVES
? Distinguish descriptive from inferential statistics ? Apply the decision path in determining statistical tests to use in data analysis ? Determine appropriate parametric or nonparametric statistical tests to use in
data analysis
Describe data
Frequencies Percentages Means (SD)
Research Purpose
Examine differences
Examine relationships
Predict relationships
2 Groups Pre-test / Post-test - t-test - Mann-Whitney U test - Wilcoxen - Chi-Squared
> 2 Groups - ANOVA - ANCOVA - MANOVA Pre-test / Post-test - RM-ANOVA
Correlation Statistic
- Pearson's r - Spearman Rho - Kendall's Tau - Chi-Square
Regression Analysis - Linear Regression - Multiple regression - Logistic regression
LEVELS OF MEASUREMENT
Nominal
? Gender ? Ethnicity ? Marital status ? Zip code ? Religious affiliation ? Medical diagnosis ? Names of medications
Ordinal
Interval
? Pain scale (0-10)
? Temperature
? Age groups (18-25, 26- ? IQ
35, etc.)
? SAT score
? Grade (A, B, C, D, & F) ? Depression score
? Satisfaction scale (poor, ? Time of day
acceptable, good)
? Dates (years)
? Performance scale
(Below average, average,
above average)
Ratio
? Age ? Height ? Weight ? BP ? HR ? Years of experience ? Time to complete a task
CATEGORIES OF STATISTICS
? Descriptive Statistics
? Inferential Statistics
? Describe situations and events ? Allows conclusions about variables
? Summary (numbers, percentages) ? Statistical tests are performed
? Central Tendency
? Charts / Graphs
? Comparisons ? Associations ? Predictions
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