Normal Curve
a theoretical frequency distribution of all possible values in a population. It is theoretical in that no naturally occurring population perfectly fits the curve.
- In a normal distribution curve, the mode, median, and mean are equal.
Level of Significance (the cutoff point)
Probability level at which the results of statistical analysis are judged to indicate a statistically significant difference between the groups
Type I Errors
occurs when the null hypothesis is rejected when it is true. (e.g., when the results indicate that there is a significant difference, when reality there is not)
Type II
Type II error (β) occurs when the null hypothesis is regarded as true but is in fact false (e.g., The results indicate there is no significant difference, when in reality there is a difference)
Power Analysis
- The level of significance (α = 0.05)
- Sample size
- Power (minimum acceptable power is = 0.80 (80%)
- Effect size (> 0.50)
Descriptive Statistics
Summarize the data. Their purpose is to determine predominant and average values, as well as sameness and differentness.
- Frequency
- Measures of Central Tendency
- Measures of Dispersion
Frequency distributions
- Ungrouped frequency distributions
- Grouped frequency distributions
- Percentage distributions
Measures of central tendency
- Mode
- Median
- Mean
Measures of dispersion
- Range
- Variance
- Standard Deviation
- Confidence Interval
- Standardized Scores
- Scatterplots
Inferential Statistics
Used to test an actual or implied hypothesis, emanating from the research purpose—those testing relationships and differences are the primary ones.
- Examining Differences (e.g., t-test, ANOVA)
- Predicting outcomes (e.g., Regression)
- Examining Relationship (e.g., Parson Product-Moment Correlation)
Examining Relationship
- Pearson Product-Moment Correlation
- Factor Analysis
Predicting Outcomes
- Regression Analysis
Examining Differences
- Chi-Square
- t-Test
- Analysis of Variance (ANOVA)
