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8.1.2.2.2 - Minitab: 1 Sample Proportion z test, Summary Data.8.1.2.2.1 - Minitab: 1 Proportion z Test, Raw Data.8.1.2.2 - Minitab: Hypothesis Tests for One Proportion.8.1.2.1.4 - Example: Overweight Citizens.8.1.2.1 - Normal Approximation Method Formulas.8.1.1.3 - Computing Necessary Sample Size.8.1.1.2.2 - Example with Summarized Data.8.1.1.2.1 - Example with Summarized Data.8.1.1.2 - Minitab: Confidence Interval for a Proportion.
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8.1.1.1.2 - Video Example: Dog Ownership.8.1.1.1.1 - Video Example: PA Residency.8.1.1.1 - Normal Approximation Formulas.7.4.2.3 - Example: 99% CI for Proportion of Women Students.7.4.2.2 - Video Example: 90% CI for the Correlation between Height and Weight.7.4.2.1 - Video Example: 98% CI for Mean Atlanta Commute Time.7.4.1.6 - Example: Difference in Mean Commute Times.7.4.1.4 - Example: Proportion of Women Students.7.4.1.3 - Example: Proportion NFL Coin Toss Wins.7.4.1.2 - Video Example: Correlation Between Printer Price and PPM.7.4.1.1 - Video Example: Mean Body Temperature.7.3 - Minitab: Finding Values Given Proportions.7.2.3.1 - Example: Proportion Between z -2 and +2.7.2 - Minitab: Finding Proportions Under a Normal Distribution.6.6 - Confidence Intervals & Hypothesis Testing.5.5.4 - Correlation Example: Quiz & Exam Scores.5.5.3 - Difference in Means Example: Exercise by Biological Sex.5.5.1 - Single Proportion Example: PA Residency.5.5 - Randomization Test Examples in StatKey.5.3.1 - StatKey Randomization Methods (Optional).5.1 - Introduction to Hypothesis Testing.4.6 - Impact of Sample Size on Confidence Intervals.4.4.2.2 - Example: Difference in Dieting by Biological Sex.4.4.2.1 - Example: Correlation Between Quiz & Exam Scores.4.4.1.2 - Example: Difference in Mean Commute Times.4.4.1.1 - Example: Proportion of Lactose Intolerant German Adults.4.3.2 - Example: Bootstrap Distribution for Difference in Mean Exercise.4.3.1 - Example: Bootstrap Distribution for Proportion of Peanuts.4.2.1 - Interpreting Confidence Intervals.4.2 - Introduction to Confidence Intervals.4.1.1.2 - Coin Flipping (One Proportion).3.5 - Relations between Multiple Variables.3.4.2.2 - Example of Computing r by Hand (Optional).3.4.2.1 - Formulas for Computing Pearson's r.3.3 - One Quantitative and One Categorical Variable.2.2.6 - Minitab: Central Tendency & Variability.2.2.1 - Graphs: Dotplots and Histograms.2.1.3.2.5.1 - Advanced Conditional Probability Applications.2.1.3.2.1 - Disjoint & Independent Events.2.1.2.1 - Minitab: Two-Way Contingency Table.1.2.2.1 - Minitab: Simple Random Sampling.
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#Anova minitab how to
In this lesson, we will learn how to compare the means of more than two independent groups. In previous lessons you learned how to compare the means of two independent groups.