PreparED Study Materials
STAT-UB 103: Stats F/Bus Cntl Regress & Forecasting Models
School: New York University
Number of Notes and Study Guides Available: 4
Notes
Videos
Actinomycin D's Impact on RNA Synthesis: An Experimental Insigh
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Explore a biologist's experiment testing the effects of actinomycin D concentrations on RNA synthesis in cells. By analyzing the outcomes and calculating p-values, this video offers insights into how higher concentrations might inhibit normal RNA synthesis.
Analyzing Salad Habits: A Statistical Look at 85.5%
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Examine a survey of 200 adults regarding salad consumption, leading to a sample proportion of 85.5%. Using hypothesis testing and z-test calculations, the video determines whether more than 85% of American adults eat salad weekly. The results offer statistical insights into dietary habits.
Analyzing Engineers' Graduate Plans: Fortune vs Engineering Horizons D
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This video contrasts Fortune's claim about engineers pursuing further studies with data from Engineering Horizons. Utilizing hypothesis testing and confidence intervals, we assess the validity of Fortune's assertion within a statistical framework.
Electronic Failures: Deciding Between Minor & Major Defects Cost-Effec
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Discover the intricacies of determining the cause of electronic system failures, either minor or major defects, using statistical distributions. Learn how to minimize the expected cost and make informed decisions based on soundings and loss tables
Margin of Error: Decoding the Uncertainty in Estimates
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Unravel the concept of the "margin of error" within the context of estimating children's exposure to lead-based paint. Through clear explanations, comprehend the importance of acknowledging uncertainty in statistical findings and how it represents a range for potential true values.
Car Theft Rates: Does Your Car Type Influence Risk?
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Explore the relationship between specific car types and their theft rates. This video assesses correlations between car models like the Honda Accord, Toyota Camry, and others, emphasizing the difference between correlation and causation.