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Statistics lessons in Birkenhead

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2 statistics teachers in Birkenhead

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2 statistics teachers in Birkenhead

English · Math · Statistics
Trusted teacher: Hello, Data scientist (statistician), I offer my help for the realization of statistical studies and the understanding of statistical methods. - make graphics, - analyze the links between the variables (several qualitative and/or quantitative variables), - compare groups of individuals, - produce all types of graphs and elaborate tables, - carry out modeling: regressions, ACP, ACM, ANOVA, FAMD, survival curves ..., - carry out tests: Student, Wilcoxon, Chi2, Fisher..., - categorize individuals (create groups of individuals according to their profile)... Quantitative and qualitative data, time series, surveys and polls... Regarding the renderings, I can make any type of graph and table, the illustrations in the ad have been cut for confidentiality reasons. I also send a document with the methodology used and the explanations for the choice of each test used. For example, you can send me a model table or graph and I can reproduce it with your data. Passionate, I have been helping people in carrying out statistical studies for 3 years (more than 100 theses, dissertations and articles produced), mainly doctors, people in thesis or resuming studies who do not have enough time to carry out the analyzes or very little knowledge of statistics. I have experience in all fields but most often I am asked to work in the fields of health and education. I have also been teaching mathematics and statistics for almost 6 years. Having a powerful computer I can perform tests and modeling on very large databases. I can carry out the studies very quickly, depending on the volume of the analyses, this can be carried out in 3 days. I code everything in R: graphs and analyses. The work carried out is returned in Excel and/or Word format and the graphics in PNG format. How do I operate? : payment is made according to the estimate: I estimate the time needed and you pay in advance or you pay by group of hours. For example: if I receive a payment for 3 hours, I send what I did after 3 hours and if I have to continue I wait to receive the next payment. Don't hesitate to ask me your questions and suggest your projects. I can sign a document to certify that your data will remain confidential if you wish, but I do not disclose it even if there is no signed document. For companies, I work with quotes and I can make invoices (self-employed status). The time taken to get to grips with the subject and discussion during the interview is counted and payment will be requested prior to any action on my part. See you soon
Math · Statistics
Dr. Keivan is a McGill University graduate with the following degrees: Master of Mechanical Engineering (McGill) Bachelor of Mechanical Engineering (McGill) Doctor of Medicine M.D (Iran) Dr. Keivan has more than 15 years’ experience in teaching many MATH, ENGR, and MECH courses for University students. He has been teaching assistant for many courses at Concordia University and McGill University in Montreal, with excellent course evaluation by students. The most featured courses are undergraduate and graduate mechanical engineering courses, and probability and statistics. Both in person and online classes are offered. For more information, you can contact Dr. Keivan at (514)4762075 Concordia Courses: COMM 215: Business Statistics COMP 233: Probability & Statistics ECON 325: Mathematics for Economists I ECON 326: Mathematics for Economists II ELEC 275: Principles of Electrical Engineering ENGR 213: Applied Ordinary Differential Equations ENGR 233: Applied Advanced Calculus ENGR 242: Statics ENGR 243: Dynamics ENGR 244: Mechanics of Material ENGR 251: Thermodynamics I ENGR 264: Signals and Systems I ENGR 273: Basic Circuit Analysis ENGR 301: Management Principals and Economics ENGR 311: Calculus and Partial Differential Equations ENGR 351: Thermodynamics II ENGR 361: Fluid Mechanics I ENGR 371: Probability and Statistics ENGR 391: Numerical Methods INDU 371: Random Processes INTE 296: Discover Statistics MATH 201: Elementary Functions MATH 202: College Algebra MATH 203: Differential and Integral Calculus I MATH 204: Vectors and Matrices MATH 205: Differential and Integral Calculus II MATH 206: Algebra and Functions MATH 208: Fundamental Mathematics I MATH 209: Fundamental Mathematics II MATH 251: Linear Algebra I MATH 252: Linear Algebra II MATH 264: Advanced Calculus I MATH 265: Advanced Calculus II MECH 211: Mechanical Engineering Drawing MECH 215: Programming for Mechanical and Industrial MECH 221: Material Science MECH 313: Machine Drawing and Design MECH 361: Fluid Mechanics II MECH 368: Electronics for Mechanical Engineers MECH 370: Modeling and Analysis of Dynamic Systems MECH 371: Fundamentals of Control Systems MECH 375: Mechanical Vibrations MECH 6121: Aerodynamics PHYS 204: Mechanics PHYS 205: Electricity and Magnetism PHYS 206: Waves and Optics PSYC 315: Statistical Analysis I PSYC 316: Statistical Analysis II SOCI 212: Statistics I SOCI 213: Statistics II STAT 249: Probability I STAT 250: Statistics STAT 360: Linear Models McGill Courses: CIVE 205: Statics CIVE 206: Dynamics CIVE 207: Solid Mechanics CIVE 290: Thermodynamics and Heat Transfer CIVE 302: Probabilistic Systems CIVE 320: Numerical Methods CIVE 327: Fluid Mechanics and Hydraulics ECON 208: Microeconomics Analysis and Applications ECON 227: Economic Statistics MATH 112: Fundamentals of Mathematics MATH 122: Calculus for Management MATH 123: Linear Algebra and Probability MATH 133: Linear Algebra and Geometry MATH 139: Calculus I with Pre-calculus MATH 140: Calculus I MATH 141: Calculus II MATH 150: Calculus A MATH 203: Principles of Statistics I MATH 204: Principles of Statistics II MATH 222: Calculus III MATH 223: Linear Algebra MATH 262: Intermediate Calculus MATH 263: Ordinary Differential Equations for Engineers MATH 270: Applied Linear Algebra MATH 271: Linear Algebra and Partial Differential Equations MATH 315: Ordinary Differential Equations MATH 316: Complex Variables MATH 323: Probability MATH 324: Statistics MATH 329: Theory of Interest MECH 210 Mechanics I MECH 220 Mechanics II MECH 240 Thermodynamics I MECH 289 Design Graphics MECH 290: Design Graphic for Mechanical Engineers MECH 309: Numerical Methods in Mechanical Engineering MECH 314: Dynamics of Mechanisms MECH 315: Mechanics III MECH 361: Fluid Mechanics I MECH 341: Thermodynamics II MECH 346: Heat Transfer MECH 383: Applied Electronics and Instrumentation MECH 393: Machine Element Design MECH 412: System Dynamics and Control MECH 419: Advanced Mechanics of Systems MECH 430: Fluid Mechanics II MECH 513: Control Systems MECH 533: Subsonic Aerodynamics MECH 542: Spacecraft Dynamics MECH 562: Advanced Fluid Mechanics MECH 605: Applied Math I MECH 642: Advanced Dynamics MGCR 271: Business Statistics MGSC 372: Advanced Business Statistics PHYS 101: Introductory Physics – Mechanics PHYS 102: Introductory Physics – Electromagnetism PHYS 131: Mechanics and Waves PHYS 142: Electromagnetism and Optics PSYC 204: Introduction to Psychological Statistics PSYC 305: Statistics for Experimental Design
Mechanical engineering · Math · Statistics
Trusted teacher: Class Description: In today's digital age, statistical analysis plays a crucial role in making informed decisions for businesses and organizations. This comprehensive statistics class, "Statistical Analysis for the Digital Age: Exploring Descriptive and Inferential Stats with Microsoft Excel," is designed to provide you with the knowledge and skills needed to navigate the world of data using Microsoft Excel. From the basics of descriptive statistics to the intricacies of inferential statistics, this course will take you on a journey through the fundamental concepts and techniques used in statistical analysis. You will learn how to collect, organize, and interpret data using the powerful capabilities of Microsoft Excel, including its worksheets, Data Analysis Tool, and the PhStat2 add-in. To enhance your learning experience, this course will focus exclusively on utilizing Microsoft Excel. Through practical exercises and real-world examples, you will develop proficiency in Microsoft Excel's built-in features and functionalities for statistical analysis. You will learn how to effectively use Excel's worksheets, leverage the Data Analysis Tool, and utilize the PhStat2 add-in to perform various statistical analyses. By the end of this course, you will have a solid foundation in statistical analysis using Microsoft Excel. You will be equipped with the skills to confidently navigate data, perform meaningful analyses, and make data-driven decisions that drive success in today's digital landscape. Key Topics Covered: Chapter 1: Introduction to Statistics • Definition of statistics • Role of statistics in data analysis and decision-making • Differentiating descriptive and inferential statistics Chapter 2: Types of Statistics • Descriptive statistics: Summarizing and describing data • Inferential statistics: Making inferences and drawing conclusions about populations based on sample data Chapter 3: Types of Variables • Categorical variables: Nominal and ordinal scales • Continuous variables: Interval and ratio scales Chapter 4: Descriptive Statistics: Measures of Central Tendency • Mean, median, and mode • Choosing appropriate measures based on data characteristics Chapter 5: Descriptive Statistics: Measures of Variation • Range, variance, and standard deviation • Interpreting variation in data Chapter 6: Descriptive Statistics: Measures of Shape • Skewness and kurtosis • Understanding the distributional characteristics of data Chapter 7: Data Visualization: Choosing the Right Chart • Histograms: Displaying the distribution of continuous data • Pie charts: Representing proportions or percentages • Column and Bar charts: Comparing categories or groups • Line charts: Visualizing trends or time-series data • Guidelines for selecting appropriate charts based on data types and analysis objectives Chapter 8: Probability and Counting • Sample Space • Events • Counting Sample Points • Probability of an Event • Additive Rules • Conditional Probability • Independence and the Product Rule • Bayes’ Rule Chapter 9: Random Variables and Probability Distributions • Concept of a Random Variable • Discrete Probability Distributions • Continuous Probability Distributions • Joint Probability Distributions Chapter 10: Mathematical Expectation • Mean of a Random Variable • Variance and Covariance of Random Variables • Means and Variances of Linear Combinations of Random Variables Chapter 11: Some Discrete Probability Distributions • Introduction and Motivation • Binomial and Multinomial Distributions • Hypergeometric Distribution • Negative Binomial and Geometric Distributions • Poisson Distribution and the Poisson Process Chapter 12: Some Continuous Probability Distributions • Continuous Uniform Distribution • Normal Distribution • Areas under the Normal Curve • Applications of the Normal Distribution • Normal Approximation to the Binomial • Gamma and Exponential Distributions • Chi-Squared Distribution Chapter 13: Fundamental Sampling Distributions and Data Descriptions • Random Sampling • Some Important Statistics • Sampling Distributions • Sampling Distribution of Means and the Central Limit Theorem • Sampling Distribution of S2 • t-Distribution • F-Distribution • Quantile and Probability Plots Chapter 14: One- and Two-Sample Estimation Problems • Statistical Inference • Classical Methods of Estimation • Single Sample: Estimating the Mean • Standard Error of a Point Estimate • Prediction Intervals • Tolerance Limits • Two Samples: Estimating the Difference between Two Means • Paired Observations • Single Sample: Estimating a Proportion • Two Samples: Estimating the Difference between Two Proportions • Single Sample: Estimating the Variance • Two Samples: Estimating the Ratio of Two Variances • Maximum Likelihood Estimation Chapter 15: One- and Two-Sample Tests of Hypotheses • Statistical Hypotheses: General Concepts • Testing a Statistical Hypothesis • The Use of P-Values for Decision Making in Testing Hypotheses • Single Sample: Tests Concerning a Single Mean • Two Samples: Tests on Two Means • Choice of Sample Size for Testing Means • Graphical Methods for Comparing Means • One Sample: Test on a Single Proportion • Two Samples: Tests on Two Proportions • One- and Two-Sample Tests Concerning Variances • Goodness-of-Fit Test • Test for Independence (Categorical Data) Chapter 16: Analysis of Variance (ANOVA) • Comparing means across multiple groups • One-way and two-way ANOVA Chapter 17: Chi-Square Test • Testing relationships between categorical variables • Assessing independence and goodness-of-fit Chapter 18: Simple Linear Regression and Correlation • Introduction to Linear Regression • The Simple Linear Regression Model • Least Squares and the Fitted Model • Properties of the Least Squares Estimators • Inferences Concerning the Regression Coefficients • Prediction • Choice of a Regression Model • Analysis-of-Variance Approach • Test for Linearity of Regression: Data with Repeated Observations • Data Plots and Transformations • Correlation Chapter 19: Multiple Linear Regression and Certain Nonlinear Regression Models • Estimating the Coefficients • Linear Regression Model Using Matrices • Properties of the Least Squares Estimators • Inferences in Multiple Linear Regression • Choice of a Fitted Model through Hypothesis Testing Throughout the course, you will engage in practical exercises, real-world examples, and data analysis tasks to reinforce your understanding of statistical concepts and techniques. You will also have the opportunity to apply these skills using statistical software tools to gain hands-on experience with data analysis. By the end of this course, you will have a solid grasp of both descriptive and inferential statistics, enabling you to confidently explore, analyze, and interpret data in various contexts. Whether you are a student, professional, or an individual seeking to enhance your data analysis skills, this course will empower you to make informed decisions based on statistical insights. Join us on this statistical journey and unlock the foundations of statistical analysis. Enroll now in the "Statistical Foundations: Exploring Descriptive and Inferential Analysis" course to develop your statistical proficiency and leverage the power of data-driven decision-making, including the use of charts for effective data visualization and interpretation.
Math · Statistics · Algebra
Trusted teacher: As a highly qualified mathematics teacher, graduate of the Teachers College and with 11 years of teaching experience in public high schools, I am happy to offer at-home mathematics tutoring courses for secondary school classes. 2nd and 1st general, Terminal specialty of the French system, as well as the 5th, 4th and 3rd levels of the college. students at level T and Common Core Sciences, TC Technological, 1st Bac Experimental Sciences and final year of all sectors (SVT-PC-SC.Math-L). My primary objective is to help students improve their level, deepen their knowledge, assimilate their lessons, fill their gaps and improve their skills in the discipline of mathematics. In addition, I am perfectly able to support them in the preparation of their exams and competitions for access to the Grandes Ecoles, and to provide them with homework help so that they can succeed in this subject. With my advanced math skills and knowledge, I am confident that I can provide my students with effective tools and techniques to help them progress. My goal is to give them confidence and help them develop a passion for mathematics, a subject that can seem daunting at first, but can be exciting and rewarding if taught in an interesting and fun way. By choosing my tutoring courses in mathematics, students can expect to receive individual attention and personalized help to overcome their difficulties and achieve their goals. My teaching approach is interactive and student-centered, which allows for a deeper understanding of mathematical concepts and a more practical application of acquired knowledge. In summary, I am confident in my skills as a math teacher to help students of all levels progress and succeed in this demanding subject. I am convinced that my dynamic and stimulating teaching methods will help my students achieve their math goals and build a confidence that will follow them throughout their lives.
Math · Algebra · Statistics
Statistics
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Physics and Mathematics: private lessons for Secondary/High School and University Students (Munich)
Lolian
I'm a first year Informatics student, and Iv'e had around 20 hours of online math lessons with Lolian in the past few weeks. I can only recommend for anyone who needs help to choose Lolian's tutoring. He always makes sure that you completely understand and follow his explanations, very professional but also careful, and tries to be always available considering both side's schedule. Thank you so much!
Review by LIRI
Mathematics, Economics (microeconomics, macroeconomics), Statistics, Probabilities (Copenhagen)
Constance
My daughter likes Consance very much. She is always on time and explains the problems so my daughter understands. My daughter feels it has made a difference with her math practice..
Review by EVA-LOTTA STRANDH
Math Courses in Brussels - Experienced Tutor - Master's at ULB in Business Engineering (Brussels)
Ryan
My son really enjoyed his time with Ryan. he is very attentive and tries his best to clearly explain things
Review by SHOQI