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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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

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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ๅ…ฑๆœ‰ๅฏ่ƒฝใช่จผๆ˜Žๆ›ธ

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ใ‚ณใƒผใ‚น่ฉณ็ดฐ

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

ใ‚ญใƒฃใƒชใ‚ขใƒ‘ใ‚น

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.

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ใ‚ณใƒผใ‚นใ‚’ๅฎŒไบ†ใ™ใ‚‹ใฎใซใฉใ‚Œใใ‚‰ใ„ๆ™‚้–“ใŒใ‹ใ‹ใ‚Šใพใ™ใ‹๏ผŸ

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ใ„ใคใ‚ณใƒผใ‚นใ‚’้–‹ๅง‹ใงใใพใ™ใ‹๏ผŸ

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ใ“ใฎใ‚ณใƒผใ‚นใฎๆ”ฏๆ‰•ใ„ใฎใŸใ‚ใซไผš็คพ็”จใฎ่ซ‹ๆฑ‚ๆ›ธใ‚’ใƒชใ‚ฏใ‚จใ‚นใƒˆใ—ใฆใใ ใ•ใ„ใ€‚

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ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
PROFESSIONAL CERTIFICATE IN DATA SCIENCE: STATISTICAL ANALYSIS
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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