PSYCH STATS

Statistics

Science of collecting, analyzing, interpreting, presenting, and organizing data. It involves various techniques and methodologies that aid in understanding and describing data.

Variable

A characteristic or attribute that can take on different values or categories, used in statistical analysis. In statistics, a variable is a measurable trait or characteristic that varies among individuals or entities in a study.

Population

A complete set of individuals or items that share a common characteristic, from which a sample can be drawn for statistical analysis.

Parameter

A numerical value that summarizes a characteristic of a population, such as mean or standard deviation, often unknown and estimated through sample statistics.

Sample

A subset of individuals or items selected from a population, used for conducting statistical analysis and drawing inferences about the population characteristics.

Data

A collection of observations or measurements obtained from a sample, used to analyze or infer information about a population.

Total Enumeration

Descriptive Statistics

Mean

Median

Mode

Range

Variance

Standard Deviation

Inferential Statistics

Sampling Error

Quantitative Data

Qualitative Data

Discrete

Continuous

Nominal

Ordinal

Interval

Ratio

Descriptive Research

Survey Research

Correlational Method

Experimental Method

Independent Variable

Dependent Variable

Experimental Condition

Control Condition

Frequency Table

Proportion

Percentage

Frequency Distribution Table

Central Tendency

Unimodal Distribution

Bimodal Distribution

Multimodal Distribution

Rectangular Distribution

Symmetrical Distribution

Skewed Distribution

Positively Skewed Distribution

Floor Effect

Negatively Skewed Distribution

Ceiling Effect

Normal Curve

Kurtosis

Leptokurtic

Mesokurtic

Platykurtic

Varability

Z-Score

Mean and Standard Deviation of Z-Scores (both population and sample)

The Normal Curve

The Normal Curve Table

3 Sigma (Emipiral) Rule

Probability

Hypothesis Testing

Null Hypothesis

Alternative Hypothesis

Level of Significance

Cut Off Sample Score

Critical Region

Directional Hypothesis

One-tailed Test

Non-Directional Hypothesis

Two-tailed Test

Standard error of the Mean (SEM)

Central Limit Theorem

Decision Errors

Type 1 Error (False Positive)

Type 2 Error (False Negative)

Effect Size

Statistical Power

Parametric Test

Non Parametric Test

Level of Measurement

Normality of Distribution

Shapiro-Wilk Test

Kolmogorov-Smirnov Test

Cohen’s d value

Homogeneity of Variance (Homoscedasticity)

Levene’s Test

Browne-Forsythe Test

Independence of Observation

Linearity

Scatter Plot

No Significant Outliers

Sphericity (Repeated Measures ANOVA)

Mauchly’s Test of Spheticity

Multicollinearity

Variance Inflation Factor (VIF)