PreparED Study Materials

STAT 7020: REGRESSION ANALYSIS

School: Auburn University

Number of Notes and Study Guides Available: 2

Study Guides

Videos

Analyzing Grade Variance: Is it More than Usual? A Chi-Square Test
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Discover the process of analyzing variance in midterm grades with a Chi-Square test. Understand the significance of high variance and its implications. Follow along as we assess a professor's suspicion about unusually varied student performance.

Job Trends Analysis: Normal Approximation & Z-Values
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Explore the nuances of determining the likelihood of specific employment patterns using statistical methods. Understand the application of the normal approximation to the binomial distribution and the role of z-values in probability determinations. Gain clarity on interpreting employment trends with the help of a standard normal table.

ACT Score Bet: Who Owes the Pizza? A 7.6% Chance Explained
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Discover the friendly bet between Leona and Fred surrounding their ACT scores and who owes who a pizza. Using statistical principles like Z-scores and the normal distribution, we'll decipher the odds of one outperforming the other by 5 points.

Crunching Car Sales Data: Size, Color, and Probability Insights
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Uncover the likelihood of different car combinations by size and color from a dealer's sales data. Learn how to calculate probabilities, from the chances of a small car being black to the odds a non-small car isn't gray. An insightful look into understanding car preferences.

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.

2010 US Gas Prices: Insights with Chebyshev’s Inequality
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Unpack the average US gasoline prices in December 2010 using Chebyshev’s Inequality. Discover the minimum percentage of gas stations within specific price deviations. Learn how prices ranged based on standard deviations from the mean.

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