Understanding Statistical Variability and Distributions
Understanding Measures of Variability
Measures of variability indicate how much scores in a distribution vary, either from the mean or across the full extent of the distribution. It represents the spread of all the scores. Four measures of variability are discussed here: the range, the average mean deviation, the variance, and the standard deviation. These measures can reveal the consistency or similarity of the scores in a distribution and the extent to which the mean truly represents all of the
Read MoreUnderstanding Disease Frequency: Incidence, Prevalence, and Public Health Measures
Definition of Proportion
- A measure that states a count relative to the size of the group.
- A ratio in which the numerator is part of the denominator.
- May be expressed as a percentage.
Definition of Rate
- A ratio that consists of a numerator and a denominator and in which time forms part of the denominator.
- Contains the following elements:
- Disease frequency
- Unit size of population
- Time period during which an event occurs
Example of Rate Calculation
Definition of Prevalence
The number of existing cases of a disease
Read MoreCore Statistical Concepts and Applications
Linear Regression: Test Scores vs. Hours Studied
Consider the following linear regression equation: Test Scores = 45 + 5(Hours Studied)
- The Test Scores variable is the outcome variable. It is what the model is trying to predict.
- Hours Studied is the explanatory variable. It is used to explain or predict changes in the test scores.
- The slope coefficient associated with Hours Studied is 5. This indicates that for every additional hour spent studying, the model predicts an increase of 5 points in the test
Statistics Concepts: Observational Studies, Bias, and Inference
Statistics Concepts and Definitions
Ex. 1:
Observational study: No cause-effect; just associations. Five Number Summary = Min, Q1, Median, Q3, Max
Factors: Explanatory variable (x). Covariance: + or – relation but not strength
Block design: Individuals sharing the same characteristic are pooled.
SRS (Simple Random Sample); Stratified: Sample distinct groups separately then combine them. Sample survey: Cross-sectional; collect data of a population at one point in time.
Multistage: Using SRS within SRSs.
Read MoreProbability Rules and Statistical Estimation Methods
Probability Theory Fundamentals
Probability Definition
Probability measures the likelihood that an event will occur.
- The probability of an event A is often denoted as P(A). It can be calculated as: P(A) = m / n
- m = number of favorable outcomes for event A
- n = total number of possible outcomes
- P(A) represents the theoretical probability of event A.
Probability is a basic tool in the study and application of statistical methods. Medicine, for instance, often involves probabilistic reasoning.
Properties of
Read MoreKey Concepts in Statistics: Data Analysis and Probability
Key Concepts in Statistics
Data and Variables
Statistics: A branch of science that deals with collecting, organizing, analyzing, interpreting, summarizing, and presenting data.
Unit/Individual: An object on which we take a measurement or observation (e.g., people, places, things).
Population: The collection of all individuals or units under consideration.
Sample: A subset of the population from which we obtain data.
Variable: Any characteristic or property of an individual.
- Quantitative Data: Numerical