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Review 1

by: Katie Notetaker

Review 1

Katie Notetaker
GPA 3.6

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About this Document

These notes are for Fall '16
Class Notes
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This 3 page Class Notes was uploaded by Katie Notetaker on Thursday July 28, 2016. The Class Notes belongs to at University of Georgia taught by in Summer 2016. Since its upload, it has received 4 views.


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Date Created: 07/28/16
Math 2600 Abney Final Review Ch. 1 1.1 Using Data to Answer Statistical Questions  What is the purpose of statistics? o Design o Description o Inference 1.2 Sample vs. Population  We observe Samples but are interested in Populations  Statistics vs. Parameters  Descriptive Statistics vs. Inferential Statistics  Random Samples 1.3 Using Calculators & Computers  Constructing Data files Ch. 2 2.1 Different Types of Data  Variables—any characteristic observed in a study.  Quantitative (Numerical) o Discrete vs. Continuous  Qualitative (Categorical) o Ordinal vs. Nominal  Good question for distinguishing between Numerical & Categorical is does it make sense to find a mean for it? 2.2 Graphical Summaries of Data  Graphs for Qualitative Data o Bar Graph o Pie Chart  Graphs for Quantitative Data o Dot Plots o Stem & Leaf Plots o Histograms  Empirical Rule on p. 60 o Box Plot o Line Plot—for two variables 2.3 Measures of Central Tendency  Mode  Median  Mean—two concepts o Leveling off (Fair Share) o Balancing Point  How are the three different measures of center affected by outliers? 2.4 Measures of Variability  Range  SAD Math 2600 Abney Final Review  MAD  Variance = Standard Deviation Squared  Standard Deviation= Square Root(Variance) 2.5 Measures of Position  Z-scores  Five Number Summary  IQR  Percentiles  Detecting Potential Outliers o IQR method o Using the Empirical Rule & Z-scores if normal 2.6 Misuses of Graphical Summaries  Adjusting the vertical scales can give a different impression.  Using Area or volume Ch. 3 Math 2600 Abney Final Review 3.1 Association between two categorical variables  Explanatory Variable & Response Variables  Contingency Tables o Conditional Proportions  Side by side bar graphs of the Conditional Proportions o Typically, the response variable is written along the horizontal axis, so that we can compare the conditional proportions to more directly compare explanatory variables.


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