Professional Certificate in Data Science: Statistical Analysis

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The Professional Certificate in Data Science: Statistical Analysis equips learners with essential skills for career advancement in today's data-driven world. This course focuses on statistical analysis, a critical component of data science, and covers topics including probability, regression, hypothesis testing, and experimental design.

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About this course

With a strong emphasis on practical application, learners will gain hands-on experience using popular data science tools such as Python, R, and Tableau. This course is essential for those looking to break into the field of data science, as well as professionals seeking to enhance their statistical analysis skills. As data science becomes increasingly important across industries, the demand for skilled professionals in statistical analysis continues to grow. By completing this course, learners will not only gain a deep understanding of statistical analysis techniques but also develop the ability to apply these skills to real-world problems, making them highly valuable to potential employers.

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Course Details

• Basic Statistical Concepts: Descriptive statistics, probability, distributions, hypothesis testing
Exploratory Data Analysis: Data visualization, data summarization, univariate and bivariate analysis
Probability Theory: Conditional probability, Bayes' theorem, random variables, joint and marginal distributions
Inferential Statistics: Confidence intervals, hypothesis testing, p-values, statistical significance
Regression Analysis: Simple and multiple linear regression, model selection, diagnostics, interpretation
Analysis of Variance (ANOVA): One-way and two-way ANOVA, factorial designs, interactions, post-hoc tests
Non-parametric Statistics: Rank-based methods, distribution-free tests, permutation tests
Multivariate Analysis: Principal component analysis, factor analysis, cluster analysis, discriminant analysis
Time Series Analysis: Autoregressive, moving average, ARIMA models, seasonality, forecasting

Career Path

This section highlights the professional relevance of statistical analysis in the data science field, featuring a 3D pie chart that showcases the distribution of popular job roles in the UK. The chart displays the percentage of job market trends for data scientists, statisticians, data analysts, machine learning engineers, and business intelligence developers. As a career path and data visualization expert, I've curated this engaging and industry-relevant content to emphasize the importance of statistical analysis in today's job market. Each role is aligned with primary and secondary keywords, reflecting current trends in the data science sector. The Google Charts 3D pie chart has a transparent background and is fully responsive, adapting seamlessly to all screen sizes. The chart is generated using plain HTML and JavaScript code, with the necessary script tag to load the Google Charts library. The JavaScript code defines the chart data, options, and rendering logic within a script block, ensuring proper layout and spacing.

Entry Requirements

  • Basic understanding of the subject matter
  • Proficiency in English language
  • Computer and internet access
  • Basic computer skills
  • Dedication to complete the course

No prior formal qualifications required. Course designed for accessibility.

Course Status

This course provides practical knowledge and skills for professional development. It is:

  • Not accredited by a recognized body
  • Not regulated by an authorized institution
  • Complementary to formal qualifications

You'll receive a certificate of completion upon successfully finishing the course.

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PROFESSIONAL CERTIFICATE IN DATA SCIENCE: STATISTICAL ANALYSIS
is awarded to
Learner Name
who has completed a programme at
London School of International Business (LSIB)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
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