Statistics for Data Science and Data Analysis

Achieve Statistical Proficiency for Data-driven insights and informed decision making

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Program Overview

The "Statistics for Data Science and Data Analysis" course is designed to provide participants with a strong foundation in statistical concepts and techniques essential for data analysis. This course will equip them with the skills to effectively analyse, interpret, and draw meaningful insights from complex datasets. 

Participants will learn how to effectively summarise and visualise data, make data-driven decisions through hypothesis testing and confidence interval estimation, build regression models to predict outcomes and analyse categorical and time-dependent data.

Uptut emphasises hands-on practice using statistical software and tools commonly used in data analysis, enabling your team to apply their knowledge to real-world data challenges. Upon completing this course, participants will acquire the vital statistical skills necessary to extract meaningful insights from complex datasets and support data-driven decision-making in various domains.

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Training Objectives

  • Develop a solid foundation in statistical concepts and terminology relevant to data science and data analysis.
  • Understand the importance of data exploration and visualization for gaining insights and identifying patterns.
  • Learn to summarize and describe data using descriptive statistics effectively.
  • Gain proficiency in probability theory and its application to data analysis.
  • Master hypothesis testing and confidence interval estimation for making data-driven decisions.
  • Acquire the skills to perform regression analysis to model relationships and make predictions.
  • Understand techniques for analyzing categorical data, such as chi-square tests.
  • Explore time series analysis methods to identify patterns and forecast future values.
  • Learn data visualization principles and techniques for effectively communicating data insights.
  • Apply statistical techniques using popular software tools commonly used in data analysis.

Core training modules

  • Introduction to Statistics and Data Science
  • Understanding the fundamental concepts and the Role of Statistics in data science.
  • Data Types and Measurement Scales
  • Exploring different data types and measurement scales used in statistical analysis.
  • Data Exploration and Visualization
  • Techniques for exploring and visualizing data to gain insights and identify patterns.
  • Descriptive Statistics
  • Summarizing and describing data using central tendency and dispersion measures.
  • Probability Theory
  • Understanding the foundations of probability theory and its application to data analysis.
  • Probability Distributions
  • Exploring discrete and continuous probability distributions and their properties.
  • Sampling and Estimation
  • Techniques for sampling data and estimating population parameters.
  • Hypothesis Testing
  • Conducting hypothesis tests to make inferences about population parameters.
  • Confidence Intervals
  • Constructing and interpreting confidence intervals to estimate population parameters.
  • Regression Analysis
  • Building regression models to understand relationships between variables and make predictions.
  • Analysis of Variance (ANOVA)
  • Analyzing variance between groups to compare means and identify significant differences.
  • Chi-Square Tests
  • Performing chi-square tests to analyze categorical data and test for independence.
  • Non-Parametric Tests
  • Applying non-parametric tests for data that does not meet the assumptions of parametric tests.
  • Time Series Analysis
  • Analyzing time-dependent data to identify patterns and trends and forecast future values.
  • Experimental Design
  • Designing experiments and analyzing the results using statistical methods.
  • Data Visualization Principles
  • Principles and best practices for effectively visualizing data to communicate insights.
  • Statistical Software and Tools
  • Utilising popular statistical software and tools like R, Python, and Excel/ Advanced Excel.
  • Ethical Considerations in Data Analysis
  • Understanding the ethical implications and responsibilities in data analysis and decision-making.
  • Case Studies and Practical Applications
  • Applying statistical techniques to real-world scenarios and data sets.
  • Communication and Reporting of Results
  • Presenting and communicating statistical findings and insights to stakeholders.

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Personalise your team’s upskilling roadmap and design a befitting, hands-on training program with Uptut

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Opt-in Certifications
AWS,, DASA & more
100% Live
on-site/online training
Labs and capstone projects
Lifetime Access
to training material and sessions

How Does Personalised Training Work?

Skill-Gap Assessment

Analysing skill gap and assessing business requirements to craft a unique program



Customising curriculum and projects to prepare your team for challenges within your industry



Supplementing training with consulting support to ensure implementation in real projects


Why Statistics for Data Science and Data Analysis for Your Business?

  • Informed Decision Making: Extract meaningful insights from your data and make informed choices that lead to better outcomes.
  • Accuracy and Reliability: Identify patterns, relationships, and trends in the data, to gain deeper insights into operations, customer behavior, market trends, and more.
  • Predictive Analytics: Forecast future trends, demand patterns, and customer behavior.

Who will Benefit from this Training?

  • Data Scientists
  • Data Analysts
  • Business Analysts
  • Data Professionals 

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Frequently Asked Questions

1. What are the pre-requisites for this training?
Faq PlusFaq Minus

The training does not require you to have prior skills or experience. The curriculum covers basics and progresses towards advanced topics.

2. Will my team get any practical experience with this training?
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With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.

3. What is your mode of delivery - online or on-site?
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We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.

4. Will trainees get certified?
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Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.

5. What do we do if we need further support after the training?
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We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.

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