BIOL 570 1nd Edition Lecture 1Outline of Current Lecture I. Introduction to course and to statisticsII. Population (parameter)a. Random sampleIII. Sample (statistic)a. Inference i. Types of inferenceIV. Types of variablesa. Explanatory and response variablesV. Types of studiesa. Observational and experimental studiesVI. Categorical vs. Numerical variablesVII. Displaying dataCurrent LecturePopulation: all units of interestSample: subset of population- Needs to represent the wholeRandom sample1. Each unit in the population has an equal chance of being chosen2. Selection of each unit is independent of each other Random Sample InferenceThese notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute. Population (parameters)Sample(descriptive statistics)Sample PopulationSample mean (statistic estimate)= Ȳ (Y bar) Population mean (parametric mean)= µȲ: value we can directly measure µ: value, we cannot measure directly, value is a constant for a particular populationSample mean will change from one sample to the next, the large the sample the betterAs sample →population, Ȳ→ µTypes of Inference1. Estimationa. Estimate is more accurate with a larger sample size2. Hypothesis testStatistics- science of understanding data and making decisions in the face of variability and uncertainty1. Defining the populationa. Relevantb. Can a random sample be obtained?2. Defining variablea. Any characteristic or measurement of individual unitData: measurements of one-or-more variables on a collection of unitsTypes of variables1. Response (dependent)a. What interests us, what we measureb. Ex. Aggressive displays, heart attack, blood pressure2. Explanatory (independent)a. What we are comparing, what might be predictedKinds of studies1. Categorical- membership in groupa. Ordinal categorical variablesi. Can be orderedb. Nominal categorical variablei. No ordering 1. Ex. Religion, sex2. Numerical- quantitative, magnitudea. Continuous numerical variablei. Ex. Mass, height, areab. Discrete numerical variablei.