VCU STAT 210 - Final Exam Study Guide (20 pages)

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Final Exam Study Guide



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Final Exam Study Guide

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An overview of the material presented in preparation for the cumulative final in statistics.


Pages:
20
Type:
Study Guide
School:
Virginia Commonwealth University
Course:
Stat 210 - Basic Practice of Statistics
Unformatted text preview:

STAT 210 1nd Edition Final Exam Study Guide Lecture 1 August 25 Statistics Science involving the extraction of information from numerical data collected from an experiment or sample Population the whole group of individuals which the researcher wants information about Parameter A characteristic of the population that a researcher wants to measure Typically denoted with Greek letters Sample A subset of the population that information is gathered from Statistic A measure calculated from data in a sample that is expressed numerically Typically denoted with symbols from regular English letters Inference A statement about a population based on the data collected in a sample Distribution A list of all possible values a characteristic can have and the number of times each value occurs Descriptive Statistics Branch of statistics dealing with ways to describe a characteristic of a population numerically or graphically and ways to compare characteristics Inferential Statistics Branch of statistics in which data and statistics are calculated from a sample to make statements about a population Replication Repetition repeated measurements Constant A characteristic whose measurements do not change when the trials are repeated Variable A characteristic whose measurements change when trials are repeated Qualitative or Categorical Variable A variable whose measurements do not vary in degree only in kind or name Quantitative Variable A variable whose measurements vary in magnitude when trials are repeated Discrete Quantitative Variable A quantitative variable whose measurements can infer only a few possible values Continuous Quantitative Variable A quantitative variable whose measurements can infer many values in a line interval Usually a measurable quantity or calculation like rates or percentages Lecture 2 August 27 Representative Sample Characteristics of the sample mimic the characteristics of the population Bias Exists when certain subjects outcomes are favored over others Selection Bias Occurs when one several types of subjects are systematically excluded from the sample Nonresponse Bias When someone is randomly chosen to be a part of a sample and fails refuses to respond or cannot be contacted Response Bias When respondents give false information or if the interviewer influences the individual s response to questions asked Haphazard Samples When a sample is collected by some sort of convenient mechanism that does not involve randomization Volunteer Response Samples When subjects volunteer to take part in a study and their responses are often strongly opinionated most often negatively opinionated Random Samples Samples in which the subjects are chosen randomly Lecture 3 August 29 Simple Random Sampling Make a list of all individuals in the population and randomly choose a certain amount n of the subjects in a way that every set of the certain amount of subjects n has the same chance of being selected for the sample Stratified Random Sampling Population split into two or more groups of like subjects called strata Simple random samples then selected from each stratum and combined Lecture 4 September 3 Experimental Units the unit of which measurements are made Treatment What is applied to experimental units Response What is measured for each experimental unit Treatment Group s Unit s that receive the treatment s Control Group units who do not receive the treatment and instead receive a fake treatment or no treatment Placebo a fake treatment given to the control group to maintain blindness Blinding When experimental units do not know to which group they belong to Double Blinding When the experimenters and experimental units do not know to which group they belong Confounding When some factor makes the treatment and control groups vary Lecture 7 September 8 Descriptive Statistics the branch of stats that utilizes numerical and graphical procedures to analyze and describe a characteristic of a population and to compare characteristics among populations In describing descriptive stats usually describe 4 things o Center of the distribution o Spread of the distribution o Shape of the distribution o Unusual features of the distribution What is the purpose of graph procedures o Simplify data o Describe distributions easily o Make statistical inferences easily Qualitative Variables variables whose measurement vary only in name or kind and cannot be ranked in order of magnitude Quantitative Variables variables whose measurement vary from trial to trial allowing for an order or ranking to be applied Stem and Leaf Plot o Know how to set up o Unusual features of the distribution for stem and leaf include any range of values not represented a concentration of data or outliers o Don t forget to state a defining rule which is like a key to define how the plot should be interpreted o Also know how to set up extended stem and leaf plots Lecture 8 September 10 Know how to set up back to back stem and leaf plots Histograms a graphical method to display quantitative data so the distribution can be described o Know how to make a histogram Lecture 9 September 12 Symmetric Distribution right and left sides of distribution are mirror images of each other Normal Distribution a type of symmetric distribution wherein the distribution is a bellshaped curve Skewed Left Distribution bell shaped curve with tail to left Skewed Right Distribution bell shaped curve with tail to right Bimodal Distribution distribution with two peaks Trimodal Distribution distribution with three peaks For distribution curves center is approximated and range of data is used as measurement of spread Outlier an value that stands out from other values and oftentimes creates a skewed distribution Lecture 10 September 15 Measures of Central Location o Mean average Population mean is the sum of all values divided by the number of individuals in the population Denoted by Greek letter Usually an unknown parameter Highly influenced by outliers Estimated by sample mean denoted by Xbar o Median middle Central value with half of values less than it and half of values more than it To calculate order data from smallest to largest count how many values there are plug into the equation n 1 2 More resistant to outliers Population median denoted by and estimated by sample median denoted by M In symmetric distributions the mean and median will be the same In skewed distributions the mean will be in the direction of the long tail while the median will stay in


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