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Brad R. Fulton, PhD and Brad R. Fulton에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Brad R. Fulton, PhD and Brad R. Fulton 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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19_Multiple Comparisons: Delving Deeper with ANOVA

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Manage episode 312022957 series 3215655
Brad R. Fulton, PhD and Brad R. Fulton에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Brad R. Fulton, PhD and Brad R. Fulton 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Dive into the intricacies of statistical analysis in this episode of "Multiple Comparisons," where we explore the process of ANOVA (Analysis of Variance) and its application to multiple comparisons in academic fields. Following our previous discussion on ANOVA basics, today we focus on identifying specific group differences after establishing that at least one group mean is significantly different from others. Our example revolves around the costs of textbooks across various academic disciplines, including arts, natural sciences, and humanities, providing a practical illustration of how ANOVA is applied in real-world scenarios.

We begin by revisiting the basics of ANOVA, explaining its role in detecting significant differences among group means using the F statistic. However, the journey doesn’t end with recognizing a difference exists—our goal is to pinpoint exactly which groups differ. To achieve this, we delve into multiple comparison methods that allow for a detailed analysis beyond the initial ANOVA findings.

Throughout the episode, we navigate through interpreting box plots and summary statistics, and discuss how these tools aid in our understanding of data distribution across groups. By comparing the mean costs of textbooks for science and humanities majors, we illustrate how ANOVA guides us in making informed comparisons and decisions based on statistical evidence.

Listeners will gain insight into the statistical techniques that help determine where significant differences lie, enabling more nuanced interpretations of data in educational and other settings. Whether you're a student, educator, or data enthusiast, this episode will enhance your understanding of how statistical analysis shapes our interpretation of complex datasets. Join us to demystify the statistics behind academic cost analysis and learn to apply these concepts effectively in your own field of study or interest.

Lecture slides and additional course material can be obtained by emailing [email protected]

  continue reading

26 에피소드

Artwork
icon공유
 
Manage episode 312022957 series 3215655
Brad R. Fulton, PhD and Brad R. Fulton에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Brad R. Fulton, PhD and Brad R. Fulton 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Dive into the intricacies of statistical analysis in this episode of "Multiple Comparisons," where we explore the process of ANOVA (Analysis of Variance) and its application to multiple comparisons in academic fields. Following our previous discussion on ANOVA basics, today we focus on identifying specific group differences after establishing that at least one group mean is significantly different from others. Our example revolves around the costs of textbooks across various academic disciplines, including arts, natural sciences, and humanities, providing a practical illustration of how ANOVA is applied in real-world scenarios.

We begin by revisiting the basics of ANOVA, explaining its role in detecting significant differences among group means using the F statistic. However, the journey doesn’t end with recognizing a difference exists—our goal is to pinpoint exactly which groups differ. To achieve this, we delve into multiple comparison methods that allow for a detailed analysis beyond the initial ANOVA findings.

Throughout the episode, we navigate through interpreting box plots and summary statistics, and discuss how these tools aid in our understanding of data distribution across groups. By comparing the mean costs of textbooks for science and humanities majors, we illustrate how ANOVA guides us in making informed comparisons and decisions based on statistical evidence.

Listeners will gain insight into the statistical techniques that help determine where significant differences lie, enabling more nuanced interpretations of data in educational and other settings. Whether you're a student, educator, or data enthusiast, this episode will enhance your understanding of how statistical analysis shapes our interpretation of complex datasets. Join us to demystify the statistics behind academic cost analysis and learn to apply these concepts effectively in your own field of study or interest.

Lecture slides and additional course material can be obtained by emailing [email protected]

  continue reading

26 에피소드

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