STATS-ANALYTICS.AB1
Even You Can Learn Statistics and Analytics
Master key statistical methods and analytics skills with hands-on practice training.
- Practice in 20 Laboratorios prácticos — nothing to install
- 19 Lecciones interactivas y 95 topics mapped to the official exam objectives
- 403 Preguntas del examen de práctica y 2 Pruebas completas
Intermediate A tu propio ritmo · 1 año de acceso 5.0/5 (109 Revisar)
20 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
19Lecciones interactivas
95Topics
20Laboratorio en vivo
403Preguntas del examen de práctica
143Tarjetas didácticas
143Glosario de términos
01 / Habilidades que obtendrás
What you will be able to do
Try Free →
No se requiere tarjeta de crédito
Fully updated to cover “Big Data” analytics and the latest applications, this beginner-friendly analytics course offers a practical introduction.
You’ll master all the key statistical techniques for fields like finance, marketing, quality, science, social science, and more. This course also features gamified test preps and hands-on labs to make sure you grasp every concept.
With hands-on labs, you’ll get to polish your skills on the latest versions of Microsoft Excel. These practice labs are packed with real-world tasks and solutions that you can apply immediately in business or other settings.
- Master statistical tools to analyze massive datasets and generate actionable knowledge.
- Learn to build and interpret compelling statistical charts and tables using Excel or OpenOffice.org Calc 3.
- Explore fundamental statistical measures like mean, median, mode, standard deviation, Z scores, skewness, etc.
- Utilize probability and probability distributions.
- Use sampling distributions and confidence intervals to represent whole populations based on smaller samples.
- Test hypotheses with powerful techniques like Z, t, chi-square, and ANOVA.
- Apply regression analysis and modeling to forecast trends based on past data.
- Employ multiple regression to build models that account for the influence of multiple variables.
Course Highlights
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19 Lecciones estructuradas Cobertura completa de los objetivos principales del curso
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20 LiveLabs prácticos Escenarios interactivos guiados con evaluación instantánea
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403 Preguntas de práctica Pruebas de evaluación con justificaciones de respuesta detalladas
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1 año de acceso completo Aprendizaje a tu propio ritmo, accesible en cualquier momento y en todos los dispositivos
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
19 Lecciones interactivas · 95 topics01 Introduction 2 topics +
- Mathematics Is Always Optional!
- Learning with the Concept-Interpretation Approach
02 Fundamentals of Statistics 8 topics +
- The First Three Words of Statistics
- The Fourth and Fifth Words
- The Branches of Statistics
- Sources of Data
- Sampling Concepts
- Sample Selection Methods
- One-Minute Summary
- References
03 Presenting Data in Tables and Charts 5 topics · 7 Laboratorio en vivo +
- Presenting Categorical Variables
- Presenting Numerical Variables
- “Bad” Charts
- One-Minute Summary
- References
7 Laboratorio en vivo in this lesson — see the labs panel →
04 Descriptive Statistics 7 topics · 3 Laboratorio en vivo +
- Measures of Central Tendency
- Measures of Position
- Measures of Variation
- Shape of Distributions
- Important Equations
- One-Minute Summary
- References
3 Laboratorio en vivo in this lesson — see the labs panel →
05 Probability 6 topics · 1 Laboratorio en vivo +
- Events
- More Definitions
- Some Rules of Probability
- Assigning Probabilities
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
06 Probability Distributions 7 topics · 3 Laboratorio en vivo +
- Probability Distributions for Discrete Variables
- The Binomial and Poisson Probability Distributions
- Continuous Probability Distributions and the Normal Distribution
- The Normal Probability Plot
- Important Equations
- One-Minute Summary
- References
3 Laboratorio en vivo in this lesson — see the labs panel →
07 Sampling Distributions and Confidence Intervals 8 topics · 1 Laboratorio en vivo +
- Foundational Concepts
- Sampling Error and Confidence Intervals
- Confidence Interval Estimate for the Mean Using the t Distribution (σ Unknown)
- Confidence Interval Estimation for Categorical Variables
- Confidence Interval Estimation When Normality Cannot Be Assumed
- Important Equations
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
08 Fundamentals of Hypothesis Testing 7 topics +
- The Null and Alternative Hypotheses
- Hypothesis Testing Issues
- Decision-Making Risks
- Performing Hypothesis Testing
- Types of Hypothesis Tests
- One-Minute Summary
- References
09 Hypothesis Testing: Z and t Tests 6 topics · 1 Laboratorio en vivo +
- Test for the Difference Between Two Proportions
- Test for the Difference Between the Means of Two Independent Groups
- The Paired t Test
- Important Equations
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
10 Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA) 5 topics · 1 Laboratorio en vivo +
- Chi-Square Test for Two-Way Tables
- One-Way Analysis of Variance (ANOVA): Testing fo...ferences Among the Means of More Than Two Groups
- Important Equations
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
11 Simple Linear Regression 8 topics · 1 Laboratorio en vivo +
- Basics of Regression Analysis
- Developing a Simple Linear Regression Model
- Measures of Variation
- Inferences About the Slope
- Common Mistakes When Using Regression Analysis
- Important Equations
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
12 Multiple Regression 7 topics · 1 Laboratorio en vivo +
- The Multiple Regression Model
- Coefficient of Multiple Determination
- The Overall F Test
- Residual Analysis for the Multiple Regression Model
- Inferences Concerning the Population Regression Coefficients
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
13 Introduction to Analytics 5 topics · 1 Laboratorio en vivo +
- Basic Concepts
- Descriptive Analytics
- Typical Descriptive Analytics Visualizations
- One-Minute Summary
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
14 Predictive Analytics 7 topics +
- Predictive Analytics Methods
- More About Predictive Models
- Tree Induction
- Clustering
- Association Analysis
- One-Minute Summary
- References
15 Appendix A: Microsoft Excel Operation and Configuration 2 topics +
- Conventions for Keystroke and Mouse Operations
- Microsoft Excel Technical Configuration
16 Appendix B: Review of Arithmetic and Algebra 1 topics +
- Symbols
17 Appendix C: Statistical Tables +
18 Appendix D: Spreadsheet Tips 2 topics +
- Chart Tips
- Function Tips
19 Appendix E: Advanced Techniques 2 topics +
- Advanced How-To Tips
- Analysis ToolPak Tips
Laboratorios prácticos Our edge
20 Laboratorio en vivos- Creating a Bar Chart
- Creating a Pie Chart
- Creating a Pivot Table
- Modifying and Refreshing the Pivot Table
- Creating a Bar Chart
- Creating a Line Chart
- Creating a Scatter Plot
- Calculating Mean
- Calculating Median and Mode
- Calculating First Quartile
- Working with Probability
- Calculating the Value of a Normal Random Variable
- Using the Poisson Distribution
- Computing Binomial Probabilities
- Calculating the Confidence Interval
- Analyzing the Hypothesis Test for the Pooled-Variance t-Test
- Analyzing the Hypothesis Test for the Chi-Square Test
- Creating a Histogram
- Using Multiple Regression
- Creating a Sparkline
Los laboratorios se ejecutan en tu navegador; no hay nada que instalar.
03 / Preguntas frecuentes
Preguntas antes de empezar
What is big data analytics?+
Big data analytics is the process of examining large columns of data to discover patterns, trends, and insights. It involves using advanced statistical techniques and machine learning algorithms to extract meaningful information from complex datasets.
Why is it important to learn statistics and analytics?+
Statistics and analytics for beginners are essential for making data-driven decisions in various fields such as business, finance, healthcare, and science.
What are the benefits of taking this course?+
By taking this course, you’ll gain hands-on experience in using statistical software and tools and pursue careers in data science, analytics, and related fields.
Will I need to buy additional software or tools for this course?+
No, you don’t need to purchase any additional software. This simple analytics and statistics learning course contains simulations and non-production virtual machines that can be assessed through your browser.
Develop Advanced Data and Statistical Skills
Get hands-on experience with big data analytics and statistical methods to solve real-world problems.
- 1 año de acceso completo
- 20 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito