PreparED Study Materials

ST 516: ST 516

School: North Carolina State University

Number of Notes and Study Guides Available: 2

Notes

Videos

Comparing Plastic Gear Strengths: Supplier 1 vs. Supplier 2 Analysis
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This video presents a comparison between two suppliers of plastic gears in terms of their mean impact strength. Using statistical tools like the two-sample t-test and confidence intervals, we evaluate which supplier offers stronger gears.

Reaction Times in Anderson's Study: Analyzing Central Tendencies
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Explore Anderson's 1999 study on how attention load impacts reaction times. Through hands-on analysis, understand the computation of mean, median, and mode from the provided data. Highlighting the significance of the median in capturing the central tendency amidst potential outliers.

Calculating Mean & Modal Class for Million-Dollar Bonuses
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Learn how to determine the mean and modal class for bonuses in millions. Understand midpoint calculations and how frequencies impact results. Gain insights into bonus distributions in the financial realm.

Uniform Data: Probabilities of Sample Means
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This video offers a comprehensive look into the discrete uniform population, analyzing a sample size of 54 selected with replacement. Through calculated steps, viewers learn how to determine probabilities for a sample mean within specified limits. Utilizing Z-scores and standard normal tables, the session illuminates statistical principles in real-world scenarios.

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.

Testing the 123-Gallon Daily Water Claim: Fact or Fiction?
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Explore the claim that average daily water consumption is 123 gallons. Using statistical testing, we evaluate a new sample against the Old Farmer’s Almanac claim. Learn how to interpret p-values and t-scores in hypothesis testing.

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