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Quantitative Reasoning: Understanding Inferential Statistics, Exams of Quantitative Techniques

A.T. Still University of Health Sciences (ATSU)Quantitative Techniques

A comprehensive study guide on the key concepts of inferential statistics, including population, sample, sampling, random error, central limit theorem, standardization, and probability. It covers important definitions, formulas, and relationships between these statistical principles. The guide aims to help students develop a strong foundation in quantitative reasoning and data analysis, which are essential skills for various academic and professional fields. By studying this document, students can gain a deeper understanding of how to draw meaningful conclusions from research data, evaluate the reliability of findings, and make informed decisions based on statistical evidence.

Typology: Exams

2024/2025

Available from 09/12/2024

DrShirleyAurora
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Quantitative Reasoning Chapter 6
Study Guide
inferential statistics -
_____________ are numerical methods used to determine whether research data support
a hypothesis or whether results were due to chance
population -
_________ is the universe of cases the researcher wants to describe.
population parameter -
___________ is a numerically valued attribute of a model for a population
census -
__________ is a complete enumeration of a population.
sample -
_________ is a subset of the population
sample statistic -
____________ is a numerical measure that describes an aspect of a sample
random sample -
__________ is a sample that fairly represents a population because each member has an
equal chance of inclusion
sampling frame -
__________ is a list of individuals from which a sample is actually selected
selection bias -
_________ is polling error in which the sample is not representative of the population
being studied, so that some opinions are over- or underrepresented
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Quantitative Reasoning Chapter 6

Study Guide

inferential statistics - _____________ are numerical methods used to determine whether research data support a hypothesis or whether results were due to chance population - _________ is the universe of cases the researcher wants to describe. population parameter - ___________ is a numerically valued attribute of a model for a population census - __________ is a complete enumeration of a population. sample - _________ is a subset of the population sample statistic - ____________ is a numerical measure that describes an aspect of a sample random sample - __________ is a sample that fairly represents a population because each member has an equal chance of inclusion sampling frame - __________ is a list of individuals from which a sample is actually selected selection bias - _________ is polling error in which the sample is not representative of the population being studied, so that some opinions are over- or underrepresented

response bias - __________ is the tendency of subjects to systematically respond to a stimulus in a particular way due to nonsensory factors random selection - __________ is a process in which subjects are selected randomly from a larger group such that every group member has an equal chance of being included in the study random sampling - __________ is a sample that fairly represents a population because each member has an equal chance of inclusion. sample statistic + random sampling error - What is the population parameter equation? variation component / sample size component - What is the random sampling error equation? standard deviation - ____________ is a computed measure of how much scores vary around the mean score range - __________ is the difference between the highest and lowest scores in a distribution

  • revisit p 131- standard deviation / square root of the sample size - How do you find random sampling error? central limit theorem -

inferential statistics - ___________ refers to a set of procedures for deciding how closely a relationship we observe in a sample corresponds to the unobserved relationship in the population from which the sample was drawn. population - A ____________ may be defined generically as the universe of cases the researcher wants to describe. population perameter - A characteristic of a population is called a ____________. μ - The population mean is symbolized by ______________. sample - A ___________ is a number of cases or observations drawn from a population. sample statistic - A characteristic of a sample, such as the mean level of support for the Democratic Party, is a. x-bar - Sample mean is symbolized by __________. procedure, variation, sample size - What are 3 factors determine how accurately x-bar estimates μ? random sample - In taking a _______________, the researcher ensures that every member of the population has an equal chance of being chosen for the sample.

random sampling error - ______________ is defined as the extent to which a sample statistic differs, by chance, from a population parameter. population parameter - _____________ = Sample statistic + Random sampling error random sampling error - ______________ =σ / √n declines - RANDOM SAMPLING ERROR INCLINES/DECLINES AS A FUNCTION OF THE INVERSE OF THE SQUARE ROOT OF SAMPLE SIZE (N). increases - As variation in the population parameter increases, random sampling error increases/decreases true - True or False? Random sampling error and standard error are synonymous. Central Limit Theorem - _____________ is the theory that, as sample size increases, the distribution of sample means of size n, randomly selected, approaches a normal distribution. standardization - _____________ occurs when the numbers in distribution are converted into standard units of deviation from the mean of the distribution. Z - _________ = ( x bar - μ ) / (standard error)