STAT 503 EXAM QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS VERIFIED LATEST UPDATE

STAT 503 EXAM QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS VERIFIED LATEST UPDATE why do we need statistics? - biologists study the properties of living things - measuring these properties is a challenge variation an inherent component of all living systems system anything composed of multiple interacting parts constraints of stats time and funding uncertainty variation + incomplete information - sampling can bring it to the project - probability or likelihood Statistics - the study of methods to describe and measure aspects of nature from samples - a branch of science chiefly concerned with the collection, analysis, interpretation, and presentation of empirical data - provides tools to turn raw data into knowledge and understanding - helps us recognize and describe the patterns in our data and helps us decide how certain we are that our data reflect reality - it is about estimation estimation the process of inferring an unknown quantity of a population using sample data - a.k.a. statistic - a related quantity calculated from a sample - approximation of the truth parameter a quantity describing a population - the truth - The numeric quantities that we use to describe a distribution model a simplified representation of some part of the real world sampling theory focuses on the generalizability of descriptive findings to the population from which the sample was drawn - a good way to organize data collection - ensures that our data are unbiased, so they give us a reliable picture of the real world, and it also helps us to do this in a way that's efficient inferential statistics numerical data that allow one to generalize- to infer from sample data the probability of something being true of a population statistical model - estimate values - test hypothesis - predict new observations - If we combine the parameters for location and spread of a distribution with an equation that describes its shape Biological, or scientific models - explain how we think a system works - They identify the important components in a system and describe how those parts interact with each other - they describe causal relationships among the different parts of the system - Because these models propose specific cause-and-effect relationships, they can make specific, testable predictions about the patterns that we should see in our data if they're correct. statistical models - describe and summarize the patterns that exist in our data, and explain how sampling error or other sources of random variation would affect those patterns. - As a result, they allow us to draw reliable or valid conclusions about patterns that exist in the real world despite the fact that we are only looking at a small number of individuals. - Describe and summarize the patterns in data. - Explain the effects of sampling error and other sources of random variation on those patterns. - Allow us to draw reliable (valid) conclusions about patterns that exist in the real world based on limited data sets. Statistical vs Biological So statistical models are tools that we use to determine whether we think that the patterns that exist in the real world match the patterns that our biological models predicted. When we do this, we're making something called an inference. study population the collection of all individual units that we want to draw conclusions about sample - a smaller group selected from the population, that we actually observe and collect data on - a subset of units taken from the population sample units (study units) The members of a population specimen a biological sample sample unit one specimen statistical sample a group of specimens collected from the same study population variables The characteristics of the individuals in the sample that we observe or measure