Statistics For Data Professionals

Enrolled : 133 students
Duration : 177
No. of Videos: 52
Categories: eLearning
Certification: Yes
Access:Lifetime
Type:Animated Video Series

Statistics is the key to unlocking the potential of data science and analytics.

By mastering statistical techniques, you can extract valuable insights from data and make informed decisions.

Our Statistics for Data Professionals course launched at Just 99 Rs is a well-curated program that covers essential concepts:

•Descriptive Statistics: Understand the basic characteristics of data.

•Probability Theory: Learn the foundation of statistical inference.

•Inferential Statistics: Make inferences about a population based on sample data.

•Regression and Correlation: Model relationships between variables.

•Time Series Analysis: Analyze time-dependent data.

•Statistical Techniques and Tools: Learn to use statistical software like R or Python.

•Real-World Applications: Explore practical applications of statistics in various fields.

Whether you are a beginner or a seasoned data professional, this affordable course (just ₹99) will help you enhance your statistical skills and advance your career.

Enrol today to embark on your statistical learning journey.

Statistics For Data Professionals

Statistics For Data Professionals

Course Features

1.Introduction to Statistics

1.1 Overview of Statistics 4.3 Min

1.1 Overview of Statistics

1.2 Data types and measurement 4.4 Min

1.2 Data types and measurement

1.3 Basic Terminology 2.5 Min

1.3 Basic Terminology

2.Descriptive Statistics

2.1 Data Collection Methods 3.0 Min

2.1 Data Collection Methods

2.2 Measures of Central Tendency 3.3 Min

2.2 Measures of Central Tendency

2.3 Measures of Dispersion 3.5 Min

2.3 Measures of Dispersion

2.4 Measures of Position 3.3 Min

2.4 Measures of Position

3.Probability Theory

3.1 Basic probability Concepts-I 5.0 Min

3.1 Basic probability Concepts-I

3.2 Basic probability Concepts-II 3.3 Min

3.2 Basic probability Concepts-II

3.3 Probability Distributions-I 3.3 Min

3.3 Probability Distributions-I

3.4 Probability Distributions-II 2.3 Min

3.4 Probability Distributions-II

3.5 Probability Distributions-III 4.4 Min

3.5 Probability Distributions-III

3.6 Conditional Probability and Bayes Theorem-I 3.2 Min

3.6 Conditional Probability and Bayes Theorem-I

3.7 Conditional Probability and Bayes Theorem-II 2.5 Min

3.7 Conditional Probability and Bayes Theorem-II

4.Inferential Statistics

4.1 Sampling techniques-I 2.3 Min

4.1 Sampling techniques-I

4.2 Sampling techniques-II 3.0 Min

4.2 Sampling techniques-II

4.3 Point Estimation and Interval Estimation 4.0 Min

4.3 Point Estimation and Interval Estimation

4.4 Hypothesis Testing-I 3.1 Min

4.4 Hypothesis Testing-I

4.5 Hypothesis Testing-II 3.5 Min

4.5 Hypothesis Testing-II

4.6 Hypothesis Testing-III 3.5 Min

4.6 Hypothesis Testing-III

4.7 ANOVA - I 4.1 Min

4.7 ANOVA - I

4.8 ANOVA - II 5.2 Min

4.8 ANOVA - II

5.Regression and Correlation

5.1 Simple Linear Regression-I 2.3 Min

5.1 Simple Linear Regression-I

5.2 Simple Linear Regression-II 3.0 Min

5.2 Simple Linear Regression-II

5.3 Simple Linear Regression-III 4.5 Min

5.3 Simple Linear Regression-III

5.4 Simple Linear Regression-IV 4.3 Min

5.4 Simple Linear Regression-IV

5.5 Logistic Regression for Binary Outcomes-I 2.4 Min

5.5 Logistic Regression for Binary Outcomes-I

5.6 Logistic Regression for Binary Outcomes-II 2.4 Min

5.6 Logistic Regression for Binary Outcomes-II

6.Time Series Analysis

6.1 Introduction to time series Analysis-I 2.5 Min

6.1 Introduction to time series Analysis-I

6.2 Introduction to time series Analysis-II 3.2 Min

6.2 Introduction to time series Analysis-II

6.3 Introduction to time series Analysis-III 2.5 Min

6.3 Introduction to time series Analysis-III

6.4 Introduction to time series components 4.0 Min

6.4 Introduction to time series components

6.5 Smoothing Techniques 3.1 Min

6.5 Smoothing Techniques

6.6 Autoregressive Models 4.5 Min

6.6 Autoregressive Models

7.Advanced Topics

7.1 Multivariate Analysis – PCA and Factor Analysis 4.0 Min

7.1 Multivariate Analysis – PCA and Factor Analysis