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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

Juan - Guayaquil, Ecuador£19
£19Statistical Analysis for the Digital Age: Exploring Descriptive and Inferential Stats with Microsoft Excel
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
(5 reviews)
Ahmed - Brussels, Belgium£56
£56Statistics Courses By a University Professor
Trusted teacher: In order to support students who encounter difficulties in statistics, remedial sessions on descriptive statistics and inferential statistics are offered in particular on: confidence interval, statistical hypothesis test, Paired data or not? "Normal" or not? Parametric and non-parametric tests, Confidence interval and "number of subjects needed" in estimating a proportion, Also the analysis of your thesis data (linear / logistic regression, anova, t-tests, principal component analysis, repeated measures, mixed models, time series, panel analyzes, fixed and random effects models, survival analysis, SEM, ...). Do you need to be accompanied to motivate you? I offer lessons to see or review together a chapter, a theme or others ... During these remediation sessions, I offer you various activities (Q&A sessions, resolution of standard exams, revision of concepts more difficult to integrate, etc.) which help students to fill in the gaps identified in previous courses. Passionate about mathematics and quantum physics, juggles with statistics on a daily basis in my BIGDATA research work, demystifies this test by the precise approach of the subjects via an adapted teaching whose key words - study methodology, - reasoning, and especially learning to reason differently - analysis and response strategies, - targeting of the problem - implementation of the link between theory and practice
Statistics
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Juan - Chile£15
£15Statistics and Probability classes at all levels
Trusted teacher: I have a degree in Statistics and have more than 10 years of experience as a teacher. I have experience in Civil Aviation, Banking, Technology and the Education Sector. I have worked on Statistical Information Systems implementation projects. What can I teach you? Consulting in data analysis and processing for assignments, theses, academic tests, exams, and homework. Topics: *Descriptive statistics: Mean, Mode, Variance, Standard Deviation, Statistical Graphs *Probabilities: Probability calculation, Continuous and discrete probability distributions (Normal, Binomial, Poisson, Gamma, Uniform, etc.) *Inferential statistics: Point estimates and confidence intervals, Hypothesis testing *Database management: SQL *Data analysis *Linear and non-linear models *Supervised and unsupervised learning (Machine Learning): Logistic regression, Kmeans, Clustering, Neural Networks, Decision trees) *Data mining *Text mining *Sampling: Selection of samples *Design of experiments What programs do I use? *R *Python *SPSS *Minitab *Orange *RapidMiner *SQL *Power BI *Canva Where do I teach my classes? Online classes via Zoom Online classes via Teams Online classes via Google Meets Languages in which I can give you classes: *Spanish *English *Portuguese My methodology: *Practical, simple and easy to learn classes. *I adapt my classes to the student's learning style, the guides and materials available to the student. *I use digital whiteboards to teach my classes. *Interactive classes. *Theoretical and practical classes. *Management of subject content, extensive experience in exams. *I can give you tips on the topics and problem solving. In addition to statistics, I can also help you with: *Mathematics and Calculus (Derivatives, Integrals, Limit Calculations, etc.) *Econometrics *Macroeconomy *Microeconomics *Algebra *Operations research *Linear programming *English *Document translation
Statistics · Math
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Our students from Rabat evaluate their Statistics teacher.

To ensure the quality of our Statistics teachers, we ask our students from Rabat to review them.
Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.6 out of 5 based on 25 reviews.

Private tuition in math, french, english beginner to advanced (Ottignies-Louvain-la-Neuve)
Coralie
Great class, always constructive and searching the way to teach something useful to my daughter. We sincerely thank you and acknowledge your concern and dedication in providing a quality education and atmosphere
Review by BORJA
Mathematics, Statistics, Python and R Programming Tutoring (Leuven)
Luana
Luana is a good teacher, she is patient and brings practical examples to understand statistical issues.
Review by GREICE
Private lessons in Maths and Statistics - English or Spanish (Solna)
Victor
Good teacher. Victor is a teacher who is able to explain your question in easy way to understand.
Review by ZEYAD

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