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Statistical Journey

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Rediscovering Statistical Marvels: Reliving my Statistical Journey As I retrace my steps down the familiar path of statistics, I can't help but feel a sense of excitement and nostalgia. You see, I hold an undergraduate degree in Psychology from Penn State, where I delved deep into statistical concepts related to the humanities. Subsequently, I pursued a master's degree in Research Administration from Central Michigan, honing my skills in managing research endeavors. However, as time passed, the demands of life led me away from the realm of numbers and formulas. While my journey took me through diverse landscapes, I've always known that the statistical marvels I encountered were old friends waiting to be rediscovered. In the day-to-day most report demand dimple frequencies.  However, I want to keep my statistical skills sharp and in the forefront of my mind!  Hence, this blog serves as my personal odyssey, a journey of rekindling my passion for statistics and reawakening my
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McNemar's Test = Measuring Twice - Categorical

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McNemar's test is a statistical test used to analyze paired categorical data. It is commonly used when you have a 2x2 table, where each subject is measured twice (before and after an intervention or under two different conditions). The purpose of McNemar's test is to determine if there is a significant difference in the proportions of two related categorical variables. In the context of the husband and wife voting habits example, let's say you have two categorical variables: "Husband's Vote" (before the intervention) and "Wife's Vote" (after the intervention). Each couple has been surveyed twice, and the responses fall into one of four categories in the 2x2 table: 1. Both Husband and Wife voted "Yes." 2. Both Husband and Wife voted "No." 3. Husband voted "Yes" and Wife voted "No." 4. Husband voted "No" and Wife voted "Yes." The null hypothesis in McNemar's test is that there is no si
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