Descriptive and Inductive Statistics using R
Course Overview
| ID | 2201001 |
| Duration | 5.0 days |
| Methods | Lecture with examples and exercises. |
| Prerequisites | no |
| Target group | Data Analysts |
Overview
Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments. Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data, or the quantitative description itself. Statistical inference (or inductive statistics) is the process of drawing conclusions from data that is subject to random variation, for example, observational errors or sampling variation. This training provides you with a substantial overview of both descriptive and inductive statistics. All topics are firstly explained in presentations with the fundamental mathematical theory and examples followed secondly by hands-on exercices.
Dates
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Learn with customized examples and content—precisely tailored to your requirements.
Your benefits at a glance
- Flexible preferred date
- Customized content
- Intensive exchange
- High practical relevance
Description
Use R and RStudio for descriptive and inductive data analysis to describe data, demonstrate properties, and test hypotheses.
Services
- Lunch / catering
- Help with hotel / travel
- Comelio certificate
- Flexible: free cancellation up to one day before
Comelio Media
Still looking for additional reading? Discover suitable specialist books in our catalog.
Content
Introduction to Statistics
Descriptive and Inductive Statistics - Uni-/Bi- and Multi-variate Statistics - Summary tables: Grouped data, Frequency distributions, Contingency tables - Statistical graphics: Bar chart, Biplot, Box plot, Histogram
Descriptive Statistics: Univariate Analysis
Location: Mean (Arithmetic, Geometric, Harmonic), Median, Mode - Dispersion: Range, Standard deviation, Coefficient of variation, Percentiles, Interquartile range - Shape: Variance, Skewness, Kurtosis, Moments
Descriptive Statistics: Bivariate Analysis
Dependence: Pearson product-moment correlation, Rank correlation (Spearman's rho, Kendall's tau), Partial correlation, Scatter plot - Linear regression: Simple linear regression, Ordinary least squares - Regression analysis: Errors and residuals, Regression model validation, Mixed effects models
Inductive Statistics: Probability Theory
Probability axioms - Probability space Sample space - Elementary event - Random variable - Probability measure - Complementary event - Joint probability - Marginal probability - Conditional probability - Independence - Conditional independence - Law of total probability - Law of large numbers - Bayes' theorem - Venn diagram - Tree diagram
Inductive Statistics: Probability Distributions
Introduction: Probability mass function, Probability density function, Probability distribution function - Discrete univariate distributions: Binomial, Poisson, Geometric, Hypergeometric - Continuous univariate distributions: Uniform, Exponential, Normal (Gaussian)
Inductive Statistics: Frequentist Inference
Unbiased estimators (Mean unbiased minimum variance, Median unbiased) - Confidence interval - Testing hypotheses - Alpha-/Beta-Error and Power
Inductive Statistics: Specific Tests
Z (normal) - Student's t-test - F - Goodness of fit (Chi-squared) - Signed-rank (1-sample, 2-sample, 1-way anova)
Instructor
Our trainer for statistics and data mining with R, Marco Skulschus, studied economics in Wuppertal and Paris and has been working for more than 10 years as a lecturer, author of specialist books on databases and data analysis, and as a consultant for statistical analysis with R. Participants in his R seminars work in marketing, quality assurance, or are (aspiring) data scientists who want to use R for statistics and data mining.
Publications
- Grundlagen empirische Sozialforschung (Comelio Medien )
978-3-939701-23-1 - System und Systematik von Fragebögen (Comelio Medien )
978-3-939701-26-2 - Oracle SQL (Comelio Medien )
978-3-939701-41-5 - MS SQL Server - T-SQL - Abfragen und Analysen (Comelio Medien )
978-3-939701-69-9