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Statistics lessons in Rabat

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18 statistics teachers in Rabat

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18 statistics teachers in Rabat

Lara Katrina - Philippines£4
£4Secondary Mathematics for age 12 and above - Algebra, Geometry, Statistics & Probability
Class/Course Description: The Secondary Mathematics course is designed to build upon the foundational knowledge acquired in earlier years of mathematics education. This course covers three core areas of mathematics: Algebra, Geometry, and Statistics and Probability. The Algebra section of this course is designed to provide students with the tools and techniques required to solve complex equations and inequalities. Students will learn to manipulate expressions, solve equations, and graph functions. This section of the course will also cover quadratic equations, systems of linear equations, and polynomials. In the Geometry section of this course, students will explore the properties of two- and three-dimensional figures. They will learn to use geometric formulas to calculate area, volume, and surface area. This section of the course will also cover topics such as congruence, similarity, and trigonometry. The Statistics and Probability section of this course will provide students with an introduction to basic statistical concepts, such as measures of central tendency and variability. Students will also learn how to calculate probability, use statistical models, and make informed decisions based on data. Throughout the course, students will be encouraged to think critically and use problem-solving strategies to apply the concepts they learn. The course will also emphasize the importance of mathematical communication and collaboration, both in written and verbal formats. Course Objectives: Upon completion of the Secondary Mathematics course, students will be able to: 1. Solve complex algebraic equations and inequalities. 2. Apply mathematical formulas to calculate area, volume, and surface area of two- and three-dimensional figures. 3. Understand the properties of geometric figures and use trigonometry to solve geometric problems. 4. Use statistical concepts and techniques to interpret and analyze data. 5. Evaluate statistical models and make informed decisions based on data. 6. Communicate mathematical concepts effectively in written and verbal formats. 7. Collaborate with peers to solve mathematical problems. Assessment: Assessment in this course will be based on a variety of methods, including quizzes, tests, homework assignments, projects, and class participation. These assessments will be designed to measure the student's understanding of the concepts covered in the course and their ability to apply those concepts in real-world situations. Grading: Grades in this course will be based on a point system, with each assessment contributing a specific number of points to the student's final grade. The grading scale will be based on a 100-point system, with the following breakdown: A: 90-100% B: 80-89% C: 70-79% D: 60-69% F: Below 60% Course Materials: Students will need access to a textbook online, a laptop for online discussions and meetings, a scientific calculator, and other materials as necessary. Course materials may also include online resources, such as videos, interactive activities, and practice exercises.
Algebra · Geometry · Statistics
William - Accra, Ghana£22
£22Research Methodology Toolkit for Biologists: The Golden Solution to Every Novice Scientist's Dilemma
Trusted teacher: Are you eager to master the foundational principles of research methodology and unlock the tools for solving complex research challenges? This dynamic and practical course is your gateway to becoming a confident and skilled researcher. Packed with engaging lessons, real-world applications, and hands-on activities, you will acquire essential skills to design, execute, and publish impactful research. Whether you are a beginner or looking to enhance your expertise, this course will empower you to confidently tackle research projects and turn your findings into publications that make a difference. Join me and take your research capabilities to the next level! SYLLABUS Module 1: Foundations of Biological Research 🔵 Lesson 1.1: Understanding the Research Process in Biology ◘ Definition and scope of biological research ◘ Types of biological research (basic, applied, translational) 🔵 Lesson 1.2: Identifying Research Questions in Biology ◘ Characteristics of impactful biological research questions ◘ Refining questions for molecular biology, ecology, genomics, etc. 🔵 Lesson 1.3: Conducting a Literature Review in Biology ◘ Identifying relevant biological journals and databases (e.g., PubMed, Web of Science) ◘ Critical analysis of biological papers Module 2: Designing Your Biological Research 🔵 Lesson 2.1: Research Design for Biologists ◘ Experimental vs. observational studies in biology ◘ Designing robust controls and replicates 🔵 Lesson 2.2: Hypothesis Formulation in Biology ◘ Writing testable biological hypotheses ◘ Defining null and alternative hypotheses 🔵 Lesson 2.3: Sampling in Biological Studies ◘ Strategies for collecting biological samples (field and lab-based) ◘ Addressing sample size in population studies and molecular analyses Module 3: Biological Data Collection Techniques 🔵 Lesson 3.1: Experimental Techniques in Biology ◘ Common lab methods (e.g., PCR, Western blotting, microscopy) ◘ Good lab practices (GLP) for reproducibility 🔵 Lesson 3.2: Fieldwork for Biologists ◘ Designing ecological surveys and biodiversity studies ◘ Tools for field sampling (e.g., GPS, quadrats, transects) 🔵 Lesson 3.3: Handling Biological Specimens ◘ Sample preservation techniques for DNA, RNA, and proteins ◘ Best practices for labeling and storage Module 4: Biological Data Analysis and Interpretation 🔵 Lesson 4.1: Introduction to Statistical Analysis for Biologists ◘ Biostatistics fundamentals (e.g., t-tests, ANOVA, regression) ◘ Using R, Python, or SPSS for biological data 🔵 Lesson 4.2: Analyzing Genomic and Proteomic Data ◘ Tools like BLAST, MEGA, and Galaxy for sequence analysis ◘ Basics of bioinformatics workflows 🔵 Lesson 4.3: Interpreting Biological Results ◘ Connecting results to biological hypotheses ◘ Identifying and discussing limitations in biological research Module 5: Writing and Publishing in Biological Sciences 🔵 Lesson 5.1: Structuring a Biological Research Paper ◘ IMRAD format tailored for biological journals ◘ Writing clear and concise methods and results 🔵 Lesson 5.2: Referencing for Biologists ◘ Citation styles in biological sciences (e.g., Vancouver, APA) ◘ Using referencing tools specific to biology (e.g., EndNote, Zotero) 🔵 Lesson 5.3: Publishing in Biological Journals ◘ Identifying target journals (e.g., Nature, Cell, Microbial Genomics) ◘ Addressing reviewer comments Module 6: Ethics and Best Practices in Biological Research 🔵 Lesson 6.1: Ethical Considerations in Biology ◘ Handling live organisms and human samples ◘ Regulatory approvals (e.g., IACUC, IRB) 🔵 Lesson 6.2: Managing Biological Data ◘ FAIR principles (Findable, Accessible, Interoperable, Reusable) for biological data ◘ Data repositories for biology (e.g., NCBI, Dryad) 🔵 Lesson 6.3: Collaboration in Biology ◘ Building interdisciplinary teams (ecologists, geneticists, bioinformaticians) ◘ Leveraging platforms like ResearchGate for biologists Module 7: Practical Toolkit and Case Studies in Biology 🔵 Lesson 7.1: Tools for Efficient Biological Research ◘ Lab-specific tools (e.g., electronic lab notebooks, ELNs like LabArchives) ◘ Visualization tools (e.g., GraphPad Prism, BioRender) 🔵 Lesson 7.2: Case Studies in Biological Research ◘ Genomic studies on antimicrobial resistance pathogens ◘ Population studies in biodiversity hotspots ◘ Analyzing molecular mechanisms in model organisms
Writing · Statistics · Biology
Dennis - Kenya£17
£17Professional Business Statistics Content Writer and Tutor
Trusted teacher: Teaching Experience: I have 5 years of experience in writing and tutoring. Have helped students with academic writing review, article writing, data analysis, technical writing, pitch decks, business plans, thesis & dissertation writing, graduation papers, research reports, business writing/statistics, and generally assignment writing. With me, you will get a clear, simple and deeper understanding of the following units: Business & Social Statistics| Micro-economics| Macro-economics| Operations Research I & II| Econometrics I, II & III| Research Methodology| Applied Statistical Methods |Theory of Estimation| Entrepreneurship| Test of Hypothesis I & II| Quality Control Methods| Decision Theory| Non-Parametric Estimation. You will also get to learn on how to use statistical concepts and softwares/languages like STATA, Tableau, SPSS, Excel and Python in analyzing business data, do forecasting, test correlations and describe the data in business terms. Besides, having me by your side a tutor, you'll stop struggling with assignment writing generally and anticipate quality scores. In addition, you will learn how to write your assignments using APA, MLA, Harvard, Vancouver referencing styles among other writing formats. Certification: I am a certified tutorial fellow. Have been accredited by the Kenya National Statistical Society. Besides, I have a certification on use and application of python in machine learning and data analysis. I have a master’s degree in economics and statistics, and a bachelor's degree in statistics and programming. This makes me a solid tutor to your education and business needs. Methodology: My teaching philosophy is simple, interactive, and easy to understand the explanations of every concept. I use a hands-on technique and am approachable to my students. I incorporate fun into my lessons when possible. And while my easy-going style is suitable for many subjects and grades, I am also able to adapt my style to the needs of the student.
Business writing · Statistics · Resume writing
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