Author name: AM

Paired-Samples T-Test

Political Parties

This research project, funded by the National Science Foundation, aimed to investigate whether there were discernible differences in political party affiliation based on age. The client recognized the significance of understanding the difference in political party preferences based on age and thus initiated this study using a comprehensive dataset of survey responses from 12,000 participants […]

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independent-samples t-test

Energy Savings

NextEra Energy sought to explore the effect of solar panel installation on homeowners’ energy savings. Recognizing the growing interest in renewable energy sources and sustainability, NextEra Energy embarked on a comprehensive research initiative to investigate whether adopting solar panels led to significant home energy savings. To address this inquiry comprehensively, we had access to a

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Two-Way ANCOVA

Marketing Strategy

Accenture Interactive hired our team because it noticed a divergence in consumer behavior and brand image associated with its various marketing strategies. We recognized the importance of understanding these differences and delved deeper into the dynamics between marketing strategies and consumer perceptions. To do so, we had access to a substantial dataset of survey responses

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independent-samples t-test

Blood Pressure

Johns Hopkins Medicine recognized the need to understand the potential impact of cancer on their patient’s health, particularly concerning blood pressure. Johns Hopkins Medicine hired our team of statistical consultants to conduct a comprehensive investigation to determine if there were significant differences in blood pressure levels between patients diagnosed with cancer and those without cancer.

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independent-samples t-test

Compound D-600

Roche embarked on a research endeavor to investigate the effect of compound D-600 on gluconeogenesis, which is a crucial metabolic process that affects human health. Roche recognized the significance of this relationship in advancing medical knowledge and drug development and sought statistical consulting to conduct a comprehensive survey-based study. We determined the sample size using

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binomial logistic regression

Cancer

Massachusetts General Hospital, a Harvard Medical School teaching hospital, approached AMSTAT consulting to investigate blood transfusions’ safety and potential health risks. Specifically, the hospital aimed to determine whether there was a significant difference in cancer risk among recipients who had undergone blood transfusions. The consulting team utilized a comprehensive survey-based study to achieve this goal,

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Paired-Samples T-Test

Bending Stiffness

Johnson & Johnson entrusted our team with conducting a research initiative to explore variations in bending stiffness and strength based on fiber diameter. The objective was to understand the relationships between these critical properties and fiber diameter, which is paramount for developing and optimizing pharmaceutical products. We determined the sample size using a robust power

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Two-Way ANCOVA

Painkillers & Chronic Pain

Novartis engaged our team to conduct a comprehensive survey-based study investigating the effect of painkillers on chronic pain management. The study’s objective was to provide healthcare providers and patients with valuable insights into the effectiveness of pain medications in managing this challenging condition. We built the research project on a substantial dataset of 11,000 patient

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One-Way ANOVA

One-Way ANOVA

One-Way ANOVA If you aim to investigate whether there are any statistically significant distinctions in the means of two or more distinct groups, you can employ a one-way analysis of variance (ANOVA). For instance, consider a situation where you wish to determine if there are variations in the performance of athletes in a track event

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binomial logistic regression

Binomial Logistic Regression

Binomial Logistic Regression Binomial logistic regression is a statistical test for predicting the likelihood of an observation belonging to one of two possible categories of a binary dependent variable. This prediction is based on one or more independent variables, which can be continuous or categorical. This form of regression shares similarities with linear regression, except

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