Anthropology

Key areas of Anthropology:

Anthropology is the scientific study of humans, their cultures, societies, and biological development across time. It seeks to understand the diversity of human experiences, behaviors, and traditions, both past and present, through various subfields like cultural anthropology, archaeology, biological anthropology, and linguistic anthropology. The discipline explores topics ranging from ancient civilizations to contemporary social practices and can be applied in areas such as heritage management, social research, public policy, and global development. Some universities may request or allow the submission of a portfolio (e.g., fieldwork, research projects, or community involvement) or additional materials that showcase your interest in anthropology.

Research Methods in Anthropology

Experiments: Controlled settings to test hypotheses and establish cause-and-effect relationships. Gathering self-reported data from large groups of people. Observing and recording behavior in natural settings.

Case Studies: sychology helps in understanding not only individual behavior but also social structures, health outcomes, and societal trends. Preferably those who taught you in relevant subjects like psychology, biology, or social sciences.

Sigmoid: Maps input to a value between 0 and 1.

ReLU (Rectified Linear Unit): Outputs the input directly if it’s positive; otherwise, it outputs zero.

Tanh: Maps input to a value between -1 and 1.

Loss Function: This function measures the difference between the network’s output and the actual target. Common loss functions include Mean Squared Error (for regression tasks) and Cross-Entropy Loss (for classification tasks). Some schools may accept AP or IB credits in psychology or related subjects like Biology or Statistics, which can help fulfill introductory course requirements.

A framework where two neural networks, a generator and a discriminator, are trained simultaneously. The generator tries to create data that looks real, while the discriminator tries to distinguish between real and fake data. When a model performs well on training data but poorly on unseen data. Techniques like regularization, dropout, and cross-validation are used to mitigate this. Admission requirements for an undergraduate Psychology program can vary by institution, but generally include a combination of academic qualifications, standardized test scores, and supplementary materials. Here’s a detailed breakdown of typical requirements: