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    Statistical Analysis for the Digital Age: Exploring Descriptive and Inferential Stats with Microsoft Excel

    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.

    Extra information

    For this remote class, you will need a computer or laptop with a stable internet connection. Prior to the class, please ensure you have the following software and tools ready:

    • Microsoft Excel: We will utilize Microsoft Excel for various exercises and data analysis tasks. If you don't already have it installed, please ensure you have Microsoft Excel or a compatible spreadsheet software available on your computer.

    During the course, I will provide detailed instructions and necessary resources to enrolled students prior to the first session. If you encounter any difficulties during the software installation process, don't worry—I will be available to assist you and ensure you're ready to dive into the world of statistical analysis.

    Get ready to explore the foundations of statistical analysis, explore data, and gain insights using Microsoft Excel. Through practical exercises you will develop proficiency in applying statistical techniques to solve problems and make data-driven decisions.

    Location

    Online via webcam

    General info

    Age:
    Adults (18-64 years old)
    Student level:
    Beginner
    Intermediate
    Duration:
    60 minutes
    The class is taught in:English, Spanish

    About Me

    Hello! My name is Juan Carlos, and I am a university professor specializing in Statistics and Calculus. With over 17 years of teaching experience, I have had the pleasure of instructing students in various subjects in both English and Spanish. I recently completed my Master's degree, further enhancing my expertise in the field.

    I pride myself on having a friendly teaching style, and I strive to create a comfortable and supportive learning environment. As your instructor, I am patient, polite, and dedicated to helping you succeed. Let's get started on your learning journey—book your first lesson with me today!

    Throughout my career, I have had the opportunity to work with students from around the world through exchange programs offered by universities. This experience has allowed me to teach a wide range of subjects, including Statistics, College Algebra, Differential Calculus, Integral Calculus, Operations Research, and Traffic Engineering—all in English.

    My classes are focused on mathematics, and I tailor them to meet the unique needs of my students. Depending on your requirements, we can work with online calculators, statistical software such as RStudio, Minitab SPSS, or other programs like POM for Windows or GAMS. If you are more comfortable with Microsoft Excel, no problem! I can adapt my teaching to suit your preferences.

    When solving exercises, I pay close attention to every detail. I incorporate variations, problem-solving strategies, and highlight common mistakes that students often encounter. My goal is to ensure you grasp the concepts fully and build a strong foundation in Statitics and Math.

    I am excited to help you master mathematics and achieve your academic goals. Don't hesitate to book a class with me. Together, we will make Statistics, Math and Algebra enjoyable and understandable!

    Education

    22/05/2033 Share data through the art of visualization Module 6 of the Google Analytics Certificate – Coursera – Google.

    28/01/2023 Intro to SQL –

    23/01/2023 Data Visualization –

    01/16/2023 Analyze Data to answer Questions Module 5 of the Google Analytics Certificate - Coursera - Google.

    05/18/2022 Process Data from Dirty to Clean Module 4 of the Google Analytics Certificate - Coursera - Google.

    08/04/2022 Prepare Data for Exploration Module 3 of the Google Analytics Certificate - Coursera - Google.

    02/16/2022 Ask Questions to make Data-Driven Decisions Module 2 of the Google Analytics Certificate - Coursera - Google.

    11/30/2021 Foundations: Data, Data, Everywhere Module 1 of the Google Analytics Certificate– Coursera - Google.

    05/15/2020 – 21/06/2020 Introducción a la Programación en Python – Coursera – Pontifica Universidad Católica de Chile.

    05/15/2020 – 21/06/2020 Introducción a los Modelos de Demanda de Transporte – Coursera – Pontifica Universidad Católica de Chile.

    05/15/2020 – 21/06/2020 Análisis de Sistemas de Transporte – Coursera – Pontifica Universidad Católica de Chile.

    05/15/2020 – 21/06/2020 Ingeniería del Tráfico – Coursera – Pontifica Universidad Católica de Chile.

    MASTER IN LOGISTICS & TRANSPORT WITH A MENTION IN OPTIMIZATION MODELS • ESPOL (Escuela Superior Politécnica del Litoral) • Graduated 2018
    As a distinguished graduate of the Master in Logistics and Transport with a Mention in Optimization Models, I possess an advanced understanding of the intricate interplay between logistics, transportation, and mathematical optimization. This comprehensive program delves beyond theoretical concepts, equipping me with a robust mathematical background that enables me to develop and apply optimization models in diverse fields, including logistics, transportation, production, and assignment. With a sharp focus on practical applications, I have gained expertise in process simulation and demand forecasting, leveraging globally recognized software programs to deliver accurate insights and efficient solutions. This rigorous academic journey has fostered my ability to address complex logistical challenges, optimize supply chain operations, and enhance transportation efficiency. Armed with this specialized knowledge, I am uniquely positioned to design innovative strategies, drive cost-effective solutions, and optimize resource allocation for organizations operating in dynamic and demanding logistics and transport environments.

    11/15 - 24/2016 Mathematical model with applications in GAMS – ESPOL- AE FCNM.

    11/12/2015 Data Analysis Tools – Coursera – Wesleyan University.

    11/11/2015 IS – 00100.b Introduction to Incident Command System ICS – 100 – FEMA (Federal Emergency Management Agency).

    11/10/2015 IS – 00453 Introduction to Homeland Security Planning – FEMA (Federal Emergency Management Agency).

    10/27/2015 Data Visualization – Coursera – Wesleyan University.

    10/13/2015 IS – 00907 Active Shooter – FEMA (Federal Emergency Management Agency).

    05/30/2015 Data Scientist’s toolbox – Coursera – Johns Hopkins University.

    06/30/2015 R Programming – Coursera – Johns Hopkins University.

    06/30/2015 Questionnaire Design for Social Surveys – Coursera – University of Michigan.

    05/20/2015 Regression Models in practice – Coursera – Wesleyan University.

    04/09/2015 Regression Models – Coursera – Johns Hopkins University.

    02/03/2015 Econometrics Methods & Applications – Coursera – Erasmus University Rotterdam.

    02/20/2010 Six Sigma Tools to improve processes – ESPOL – AME.

    ECONOMIST • ESPOL (Escuela Superior Politécnica del Litoral) • Graduated 2000
    As an accomplished economist with a strong foundation in statistical analysis, I possess the expertise to meticulously examine and interpret economic variables. With an extensive understanding of statistical methods, I excel in conducting rigorous numerical and trend analysis to derive valuable insights into complex economic phenomena. Equipped with advanced statistical techniques, I adeptly uncover patterns, relationships, and correlations within data, enabling me to make informed decisions, identify market trends, and formulate effective strategies. My ability to harness the power of statistical analysis empowers me to provide accurate forecasts, evaluate economic risks, and drive evidence-based solutions for optimizing financial performance. With a relentless passion for statistics and its transformative potential, I continuously refine my skills to stay at the forefront of data-driven economic analysis.

    Experience / Qualifications

    I have worked with Undergraduate and Postgraduate students from Japan, Spain, Chile and USA. Currently I am working with a student from Spain and another from Japan reviewing basics of Statistics, Data analysis using both Microsoft Excel and RStudio.

    INSTITUTO TECNOLÓGICO BOLIVARIANO – ITB • SECTOR: EDUCATION • 10/17/2019 – NOWADAYS
    Faculty at Instituto Tecnológico Bolivariano de Guayaquil, School of Transport. Subjects I teach include Operations research in Transport, Intelligent Transportation Systems and Traffic Management and Modelling.

    MEGA APOLO • SECTOR: EMPRESARIAL • 08/05/2019 – 09/30/2019
    Purchase chief at Mega Apolo. Responsible of merchandise purchases, receipt and registration of collections from sales representatives, product conversion.

    UNIVERSIDAD TECNOLÓGICA EMPRESARIAL DE GUAYAQUIL – UTEG • SECTOR: EDUCACIÓN • 07/08/2019 – 01/2020
    Faculty at Universidad Tecnológica Empresarial de Guayaquil. Subjects I have taught include Tecnología del medio de transporte, Tecnología de la Carga, Operaciones del medio de transporte.

    PEAK PERFORMANCE INTERNATIONAL • SECTOR: EDUCATION • SAT MATH TUTOR • 06/14/2014 – 06/15/2015
    Helped students with their preparation for the mathematical section of the SAT.

    UNIVERSIDAD DE ESPECIALIDADES ESPÍRITU SANTO – UEES • SECTOR: EDUCATION • FULLTIME FACULTY • 11/2007 – 02/28/2014
    Statistics and Calculus teacher for ICP (International Careers Program – UEES – (593)42835630), subjects I taught include Calculus 1 & 2, Statistics 1 & 2. For stats I used Microsoft Excel and whenever possible software statistical packages such as SPSS and Minitab. All of these subjects were taught in English.

    PRESENT LINGUISTIC CORPORATION • SECTOR: EDUCACIÓN • COORDINATOR ASSISTANT & ENGLISH TEACHER • 05/12/2002 – 05/04/2004
    Customer service, staff management, schedule programming, conflict management and English classes.

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    • Instructor since June 2023
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    Good-fit Instructor Guarantee


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    Houssem Eddine
    A Maths teacher gives lessons in Maths, Algebra and Geometry. 7 years of experience in private lessons.
    An experienced teacher at your disposal for: - Methodology adapted to all levels. - Upgrading. - Consolidation of achievements. - Preparation for an examination / competition (CEB, CE1D, CESS.etc). - Help with homework and lessons. - Complementary exercises and review as controls and exams approach. - Advice and supervision at the level of working methods. - Recommended teaching methods. Currently, I am doing my maths aggregation. I am already an electromechanical engineer, graduated as a senior technician in electronics and electrical engineering and who passed my bachelor's degree in mathematics with honors. I teach in different technical fields and especially mathematics, algebra and electronics. At the level of my teaching methods, I use those that are advised pedagogically, I always try to explain and detail as much as possible the courses and I do not pass to the following stages until after making sure that the student understood what I explained. As a teacher, I already have good experience teaching with students for 7 years. What is certain is that I always make sure to go as far as possible to explain the exercises.

    Marko
    Math Tutoring (SAT/ACT, GMAT/GRE, IB DP MYP, Cambridge IGCSE, AS, A Level)
    Certified IB DP Math teacher. Substantial experience teaching IB (DP, MYP) curriculum as well as Cambridge International (IGCSE, AS, A Level) curriculum. SAT/ACT and GRE/GMAT prep courses through private tutoring for domestic and international students. I also teach college courses such as Calculus, Multivariable Calculus, Linear Algebra, Geometry etc. ***given the current epidemiological situation, classes are held online only, via Zoom platform. Časovi matematike za sve nivoe obrazovanja sa akcentom na internacionalni program i pripremu za SAT/ACT i ostale pristupne testove. ***Uzevši u obzir aktuelnu epidemiološku situaciju, časovi se drže isključivo online, preko Zoom platforme.

    Volodymyr
    Statistics and R – from (Uni) classes to a Dissertation, by a Cambridge Grad
    Statistics provides a valuable framework for analysing data and formalising how to derive conclusions from it. It is based on a very mathematical fundament, but stretches out to out-of-the box methods available in every computer. For whom: - You have a School class in Statistics or R - You are writing a BSc/MSc Dissertation and you are lost: for example, you have a questionnaire and you need to analyse the data in there to write your thesis. - You have practicals or need Stats for work. You can learn: - If required, mathematical foundations, formulas and logic underlaying statistics - What is a p-value, what do all these words like factor analysis, normal distribution and test ACTUALLY MEAN and WHY do we need those? - How to import your dataset and analyse it with R.

    Clement
    Mathematics / Further Mathematics Tutor (A level, GCSE and SATs)
    Are you ready to take your mathematical skills to the next level? As a university economics student at the LSE, with advanced knowledge in statistics, algebra, and mathematical methods, I’m here to help you succeed in: Building a strong foundation in algebra, geometry, and calculus. Mastering challenging topics like trigonometry and differential equations. Preparing for exams with personalised strategies tailored to your needs. With my experience as a tutor and a keen understanding of analytical problem-solving, I’ll ensure each lesson is clear, engaging, and impactful. I took A levels in Mathematics (94% A*), and Further maths (92% in core pure, 89% in stats) Let’s unlock your full potential and achieve your academic goals—get in touch today!