Data Literacy Fundamentals
Practical data literacy for industrial, energy and office roles: data types, populations and samples, descriptive statistics in plain language, correlation versus causation, data quality and the common ways numbers mislead.
55m
Общее время
4
Уровни компетенций
12
Уроки
Чему вы научитесь
- Explain what data literacy is and why every role, technical or not, now depends on it
- Classify data as categorical or numerical, discrete or continuous, and distinguish a population from a sample
- Interpret means, medians and measures of spread, and recognise when an average misleads
- Challenge causal claims made from correlated data using confounders and alternative explanations
- Assess data against the accuracy, completeness, timeliness and consistency quality dimensions
- Frame a precise question before requesting data, and handle personal data ethically and lawfully
Программа
Проходите уровни компетенций по порядку.
1
Awareness
- 3mWhat Data Literacy Is and Why Every Role Needs ItЗнания
- 3mTypes of Data, Populations and SamplesЗнания
- 7mAwareness Check: Data BasicsОценка
2
Knowledge
- 3mDescribing Data in Plain TermsЗнания
- 3mCorrelation Is Not CausationЗнания
- 8mKnowledge Check: Summaries and Causal ClaimsОценка
3
Skill
- 3mAsking a Good Question and Checking Data QualityЗнания
- 3mTurn a Vague Request into an Answerable Data QuestionЗадание
- 8mSkill Check: Questions and Data QualityОценка
4
Mastery
- 3mHow Data Misleads, and Using It EthicallyЗнания
- 3mAudit a Decision-Making Report and Brief Its OwnerЗадание
- 8mMastery Check: Judgement with DataОценка
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