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Stat 2000 Test 1 Study Guide

by: Michelle H.

Stat 2000 Test 1 Study Guide STAT 2000

Marketplace > University of Georgia > Statistics > STAT 2000 > Stat 2000 Test 1 Study Guide
Michelle H.
GPA 4.0

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About this Document

This study guide includes an overview of all vocabulary as well as all equations that are needed on the exam. If you would prefer to only study the vocabulary, I am also offering flash cards!
Intro Statistics
Georgia Gilbert
Study Guide
Statistics, Stats, intro to statistics
50 ?




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This 7 page Study Guide was uploaded by Michelle H. on Friday September 9, 2016. The Study Guide belongs to STAT 2000 at University of Georgia taught by Georgia Gilbert in Fall 2016. Since its upload, it has received 733 views. For similar materials see Intro Statistics in Statistics at University of Georgia.


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Date Created: 09/09/16
Stat. 2000 Study Guide: Test 1    Most Important Concepts  ● What a ​ ­Score​ is and how to calculate it.  ● How to use the ​1.5xIQR Rule​ to identify outliers  ● Understand what a ​residual​ is and its significance  ● Identify all types of ​studies  ● Understanding of all​ ocabulary        Calculations    ● Finding the Interquartile Range:​ Subtract the ​third quartile​ (Q3) from the ​first quartile​ (Q1)  ○ 50% of all values within the data set fall within the IQR.  ● Identifying Outliers:​ Any values that are ​less​ than ​Q1­1.5(IQR)​ or ​greater​ than  Q3+1.5(IQR)​ are considered outliers  ○ This is called the ​1.5x IQR Rule  ● Finding the Quartiles  ●   ○ σ ​ represents th​ tandard deviation  ○ μ​ represents the ​mean.​     ● Z­Score:    ○ The Z score is used to calculate how many standard deviations a value falls from the  mean.  ○ Positive scores are above the mean and negative scores are below the mean.  ● Determining the Strength of a Correlation Coefficien ​ t: ​ The correlation coefficie​ , is r i​ terpreted using the equation ​­1<​ r <1  ○ Values closer to ​ 1​ show a stron​ egative correlation  ○ Values closer to ​ ​ show a strong ​positive correlation  ○ If ​r=0​, then the variables have ​no correlation.​         Vocabulary    Experimental Study​: Researchers manipulate variables within the study in order to gather their  data. This method ensures that no outside factors can be used to explain the results obtained, and is  used to determine cause and effect relationships between variables    Observational Study​: Researchers observe data that the subjects exhibit naturally. The researcher  cannot manipulate the subject or variables in any way, and this method cannot determine cause and  effect relationships    Simple Random Sampling: ​A sampling method in which each member of the population has an  equal chance of being selected to participate in the study.    Stratified Sampling​: A sampling method in which researchers divide the population into groups  based on common characteristics such as height or age. Then, subjects are randomly selected  within each group to participate in the study.    Cluster Sampling​: A method of sampling in which the population is divided into random groups.  Then, a group is randomly selected and all members of this group participate in the study.    Systematic Sampling​: A method of sampling in which subjects are selected from the population  using an unbiased rule. For example, researchers would select every 10th member of the population  to participate.    Convenience Sampling​: A flawed method of sampling in which the subjects are individuals that are  the easiest to contact.        Undercoverage:​ This refers to group(s) in the population that are not represented in the study    Sampling Bias:​ This bias is caused by selecting subjects from the population in a method that isn’t  random or when undercoverage is present.    Nonresponse Bias:​ A bias that occurs when subjects either cannot be reached or refuse to  participate in the survey.    Response Bias​: A bias that occurs when participation in a survey is voluntary, so members of the  population that respond may have strong opinions about the survey topic that are not present in the  majority of the population.    Statistics​: The science of learning from data.  Design​: The method in which the research data is gathered  Description​: A summary of the data obtained from the study and any correlations that have been  discovered.    Inference​: Using data that has been previously obtained to make predictions or decisions.        Population​: Every member of the group the researcher is interested in studying    Sample​: The amount of the population in which researchers obtained data. This is made up of the  subjects.    Subject:​ A member of the population that participates in the study. These individuals make up the  sample.    Parameter:​ A characteristic or value that a researcher would like to obtain from the population, such  as the average income of every person living in Georgia. This is usually impossible to obtain.    Statistic​: A numerical value that summarizes the data researchers have collected from the subject.    Experimental Unit​: The individual whom is studied by the survey.    Treatment:​  A condition applied to the subject.    Explanatory Variable​: A variable in the study that explains the changes a researcher has observed.    Response Variable​: The variable in the study which data is collected from by researchers.        Placebo​: A “dummy” treatment given to the control group so they aren’t aware which treatment they  are receiving.    Double Blind​: A research method in which neither the researchers or the patients know which group  is the control group or the experimental group.    Single Blind​: A research method in which the researchers know which group is the experimental or  control, but the patients don’t.    Confounding​: A condition that occurs when multiple explanations can be given for the results  gathered by the study. This prevents researchers from determining a cause and effect relationship  between variables.    Random Design​: Subjects in a study are randomly assigned to either the placebo group or a  treatment group.    Matched­Pairs Design​: Subjects participate in the experiment in pairs. These pairs were already  related in some way before the start of the study, such as a husband and wife.    Blocking​: Researchers separate the subjects into homogeneous groups and the study is performed  on both groups separately. For example, the researchers could create a male group and a female  group.        Variable​: A characteristic or observation that is studied    Categorical Variable​: A variable that has a finite set of responses, such as a yes or no question.    Quantitative Variable​: A variable with a numerical value that cannot be put into a finite number of  groups, such as a student’s SAT score.    Skewed​: A graph that is not equally distributed on both sides.    Symmetrical:​  A graph whose values are equally distributed.    Mode​: The tallest bar on a graph and is also referred to as a peak.    Mean​: The average of all values in a data set    Median​: The value that falls in the exact middle of the data set.    Range​: The difference between the largest value and the smallest value in a data set.        Standard Deviation​: A calculation that represents how far the observations fall from the mean.    First Quartile​: The quartile that contains 25% of all data gathered    Second Quartile:​  The quartile that contains 50% of the data    Third Quartile​: The quartile that contains 75% of the data.    Interquartile Range​: A calculation of the distance between the first and third quartiles. This is  calculated by the equation Q3­Q1    Outliers​: Observed values that fall beyond the normal range of the data. They can be identified  using the 1.5(IQR) method.    Z Score​: A calculation of how many standard deviations from the mean a value lies. It is calculated  by subtracting the observed value from the mean and dividing by the standard deviation.      Positive Association:​ If the value of the explanatory variable increases, the value of the response  variable increases as well.    Negative Association​: When the value of the explanatory value increases, the response variable  decreases    No Association​: The response variable and the explanatory variable show no relation.    Correlation Coefficient:​ A numerical value that is used to determine the strength of a relationship  ​ between two variables and is evaluated using the equation ­1< r   Residual​: The difference between the actual value and the predicted value.  ● A ​positive​ residual means that the predicted value was ​too small  ● A ​negative​ residual means that the predicted value was ​too large​.      A: Using Position to Determine Variability   ● Percentile:​ Means that x percent of all observations fall at or below that value  ● Data is separated into three groups called ​quartiles.​ They split the data set into four parts,  with each part containing 25% of the observed values.  ●     ● Interquartile Range (IQR):​ The distance from Q1 to Q3.    ● Outliers:​ Observations that are either much larger or smaller than the majority of values that  are observed  ○ Outliers are detected by using the​ .5xIQR method  ■ Observations that are less than ​Q1­1.5(IQR)​ or greater than ​Q3+1.5(IQR)​ are  classified as outliers.      B: Using Shape to Determine Variability   Looking at the overall shape of the histogram allows us to observe the trends found in the data and  interpret the meaning of the study.  ● Skewed​: not symmetric, meaning the graph is not equal on both sides. Skewed histograms  are either right skewed or left skewed.  ● Symmetrical​: The graph shows equal distribution across the values  ● Mode​: The tallest bar in the graph, also known as a peak. Histograms can contain multiple  peaks  ○ If the graph has one peak, it is called ​unimodal  ○ Two peaks are ​bimodal​, three peaks are trimodal, etc.  ● Tails​: The collection of bars on either side of the mode  ○ Symmetrical graphs have tails of equal length  ○ Right skewed graphs have a longer tail on the right side  ○ Left skewed graphs have longer tails on the left side      The above histograms are described as:  ● A​: Unimodal and right skewed  ● B​: Unimodal and left skewed  ● C​: Unimodal and symmetrical           


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