Understanding Statistics STAT 111
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This 2 page Study Guide was uploaded by Lilly Rutherford on Saturday September 12, 2015. The Study Guide belongs to STAT 111 at West Virginia University taught by Sarah Quesen in Fall. Since its upload, it has received 77 views. For similar materials see /class/202821/stat-111-west-virginia-university in Statistics at West Virginia University.
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Date Created: 09/12/15
Summary of Key Concepts for STAT 111 Comprehensive Final Exam Knowing about statistical methods will have practical consequences in your everyday lives Experiment versus Observational Study Common Terms 0 Individuals Population Sampling Frame Sample Sample Survey Census Variable Convenience Sampling Voluntary Response Sampling Simple Random Sampling Parameter versus Statistic Bias and Variability Margin of Error Ask questions when you read about studies Sampling amp Nonsampling Errors 0 Concerns when asking survey questions Stratified Sampling Cluster Sampling Systematic Sampling Multistage Sampling Critical evaluation of an experiment or observational study Common terms 0 explanatory vs response variables 0 treatments randomization Randomized experiments 0 basic principles and terminology 0 problem with confounding variables DoubleBlind Experiment Difficulties and Disasters Experimental Designs Basic data ethics Confidential vs Anonymous Clinical trials Valid Measures Rates and Counts Predictive Validity Reliable Measures Critical thinking about believing the data 0 Missing information o Inconsistencies in data 0 Implausible data 0 Incorrect arithmetic 0 Hidden agendas Categorical and Quantitative Variables Distributions Pie Charts Bar Graphs Line Graphs Techniques for Making Good Graphs Stemplots amp Histograms Graph Shapes o Symmetric o Skewed to the Right 0 Skewed to the Left Outliers Population values are distributed with differing shapes some normal some nonnormal Empirical Rule quot6895997 Rule Standardized Score Zscore Percentile Statistical vs Deterministic Relationships Statistically Significant Relationship Strength amp Direction of Linear Relationship Pearson Correlation Coefficient Problems with Correlations Least Squares Regression Equation R2 Correlation does not imply causation Reasons variables may be correlated Personal probability Longrun RelativeFrequency interpretation of probability Basic probability Rules 0 Complement rule 0 Addition rule for disjoint events 0 Multiplication rule for independent events Relative Risk Longrun Relative Frequency Interpretation of Probability Law of Large Numbers Expected Value computation Rule for Sample Proportions Central Limit Theorem Compute and interpret confidence intervals for population proportions based on sample proportions Interpret Confidence Intervals for Means Hypothesis Testing 0 Find Ho and Ha o Interpret a test statistic o Interpret a pvalue Difference between a statistically significant effect and a practically important one Large Samples and Statistical Significance Small Samples and Statistical Significance Multiple Tests and Statistical Significance
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