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Interpreting Statistical and Practical Significance in Study Data Analysis

This guide focuses on generating content by interpreting study data in IPHY 3700. We will explore how to evaluate the statistical and practical significance of data, using Golay et al.'s study as a reference point. Understanding P-values and their implications—how sample size and variability affect them—is critical. We'll also interpret specific results from various studies, including the significance of the thermic effect of high-protein versus high-carbohydrate meals. This process involves recording insights in goal-based notes for effective learning.

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Interpreting Statistical and Practical Significance in Study Data Analysis

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  1. Friday, September 19 Generating Content through Interpreting Study Data IPHY 3700 Writing Process Map

  2. Process Activity: Generating Content through Interpreting Research Data Interpret the statistical significance of study data. Interpret the practical significance of study data. Record the ideas from your interpretation in goal-based notes.

  3. Results from Golay et al.’s Study Golay et al.

  4. Guidelines for Interpreting Statistical and Practical Significance A P value is the probability of obtaining your study's result (or a more extreme result) under the assumption that the null hypothesis is true. In other words, a P value is the probability of obtaining your study's result (or a more extreme result) by chance. P values are strongly influenced by sample size and the variability of individual data points. As sample size increases and variability decreases, P values decrease; so, in these conditions the probability of obtaining statistically significant results increases. P values never indicate the practical significance of study data; so, small P values never indicate great "importance" of study data. Study data may be statistically significant but practically insignificant. Study data that are not statistically significant (e.g., P > .05) can sometimes be practically significant. To interpret the practical significance of study data you have to know your science and your math! Handout: A Brief Explanation of P Values

  5. Interpret Golay et al.’s Results Golay et al.

  6. Conversions of Golay et al.’s Results To convert mmol/L of glucose to mg/dL, multiply by 18To convert mmol/L of cholesterol to mg/dL, multiply by 39To convert mmol/L of triacylglycerol to mg/dL, multiply by 89

  7. Interpret Johnston et al.’s Results The thermic effect was significantly greater for the high-protein meal versus the high-carbohydrate meal at breakfast and dinner.

  8. Interpret Latner & Schwartz’s (1999) Results

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