PreparED Study Materials

ST 351: Intro to Statistical Methods

School: Oregon State University

Number of Notes and Study Guides Available: 11

Notes

Study Guides

Videos

011 Car Colors in North America: Trends & Visual Insights
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Discover the trends in car colors for North America in 2011. Break down the percentage distribution of various shades, from dominating whites to the less frequent greens. Understand the best visual techniques to represent this data, weighing the pros and cons of graphs.

Poisson Distribution in Event Count & Uranium Discovery
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Explore the dynamics of Poisson distribution using both theoretical understanding and a practical application related to discovering uranium deposits. With the help of Bayes' formula and parameter adjustments, interpret various probabilities and outcomes for event occurrences.

Evaluating Tornado Length Claims: A Statistical Breakdown
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Explore a statistical approach to analyze the claim about average tornado lengths. Understand the nuances of hypothesis testing, from setting null and alternative hypotheses to interpreting P-values. Witness a comprehensive breakdown of the evidence from a sample of 500 tornadoes.

Understanding Null vs Alternative Hypotheses in Real-world Scenarios
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Explore various scenarios and understand the fundamental principles of the null and alternative hypotheses in statistical testing. This video breaks down how these hypotheses represent current beliefs and potential deviations, aiding in the interpretation of statistical findings.

Battery Lifetimes: Mean, Variance & Standard Deviation
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Discover the nuances of analyzing battery lifetime data through mean, variance, and standard deviation computations. Using class boundaries, midpoints, and frequencies, gain insights into the dispersion of battery lifespans and the average deviation from the mean.

Estimating Study Hours: A 99% Confidence Method"
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Explore how a university dean estimates freshmen study hours using statistical methods. Understand the importance of z-scores, confidence levels, and sample sizes in making accurate predictions. Learn how to ensure results are within a desired error margin.

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