Overview
This lecture introduces key concepts in psychological statistics, focusing on how researchers collect, describe, and interpret data to understand behavior.
Types of Data Collection
- Psychologists use quantitative research (numerical data) and qualitative research (descriptive, non-numerical data).
- Quantitative research uses tools like Likert scales to measure responses numerically.
- Qualitative research gathers in-depth insights through interviews or open-ended questions.
Measures of Central Tendency
- Central tendency summarizes what is typical in a data set.
- Mean is the average of all scores.
- Median is the middle value when scores are ordered.
- Mode is the value that appears most frequently.
Measures of Variability
- Variability shows how spread out scores are in a data set.
- Range is the difference between the highest and lowest scores.
- Standard deviation measures how much scores differ from the mean.
Distributions of Data
- Normal distribution (bell curve) is symmetrical, with most scores near the mean.
- In a normal distribution, mean, median, and mode are equal.
- 68% of scores fall within one standard deviation, 95% within two, 99.7% within three (68-95-99.7 rule).
- Skewed distributions occur when data are lopsided; positive skew tails right, negative skew tails left.
Inferential Statistics & Significance
- Inferential statistics help test hypotheses and draw broader conclusions from data.
- The p-value indicates the probability results happened by chance; p < 0.05 is considered statistically significant.
- Effect size indicates the real-world importance of a statistically significant difference.
Key Terms & Definitions
- Quantitative research — research using numerical data.
- Qualitative research — research using non-numerical, descriptive data.
- Mean — the average value in a data set.
- Median — the middle value in an ordered data set.
- Mode — the most frequently occurring value.
- Range — difference between highest and lowest values.
- Standard deviation — measure of how spread out the data are from the mean.
- Normal distribution — symmetrical, bell-shaped frequency curve.
- Skewness — measure of asymmetry in a data distribution.
- P-value — probability result occurred by chance.
- Statistical significance — result likely not due to chance (p < 0.05).
- Effect size — measure of how meaningful a result is.
Action Items / Next Steps
- Review definitions of key statistical terms.
- Practice identifying types of distributions and calculating measures of central tendency and variability.
- Read the next assigned chapter on inferential statistics.