Cursos de Pensamento Estatístico para Líderes

Nossos Clientes

Código do Curso

statdm

Duração

7 horas (usualmente 1 dia incluindo pausas)

Requisitos

Good maths skills are required. Exposure to basic statistics (i.e. working with people who do the statistical analysis) is required.

Visão geral

Este curso foi criado para tomadores de decisão cujo objetivo principal não é fazer o cálculo e a análise, mas entendê-los e ser capaz de escolher que tipo de métodos estatísticos são relevantes no planejamento estratégico da organização.

Por exemplo, um participante em potencial precisa decidir quantas amostras precisam ser coletadas antes de decidir se o produto será lançado ou não.

Se você precisar de um curso mais longo, que cubra os conceitos básicos do pensamento estatístico, dê uma olhada no treinamento de 5 dias de " Statistics para gerentes".

Machine Translated

Programa do Curso

What statistics can offer to Decision Makers

  • Descriptive Statistics
    • Basic statistics - which of the statistics (e.g. median, average, percentiles etc...) are more relevant to different distributions
    • Graphs - significance of getting it right (e.g. how the way the graph is created reflects the decision)
    • Variable types - what variables are easier to deal with
    • Ceteris paribus, things are always in motion
    • Third variable problem - how to find the real influencer
  • Inferential Statistics
    • Probability value - what is the meaning of P-value
    • Repeated experiment - how to interpret repeated experiment results
    • Data collection - you can minimize bias, but not get rid of it
    • Understanding confidence level

Statistical Thinking

  • Decision making with limited information
    • how to check how much information is enough
    • prioritizing goals based on probability and potential return (benefit/cost ratio ration, decision trees)
  • How errors add up
    • Butterfly effect
    • Black swans
    • What is Schrödinger's cat and what is Newton's Apple in business
  • Cassandra Problem - how to measure a forecast if the course of action has changed
    • Google Flu trends - how it went wrong
    • How decisions make forecast outdated
  • Forecasting - methods and practicality
    • ARIMA
    • Why naive forecasts are usually more responsive
    • How far a forecast should look into the past?
    • Why more data can mean worse forecast?

Statistical Methods useful for Decision Makers

  • Describing Bivariate Data
    • Univariate data and bivariate data
  • Probability
    • why things differ each time we measure them?
  • Normal Distributions and normally distributed errors
  • Estimation
    • Independent sources of information and degrees of freedom
  • Logic of Hypothesis Testing
    • What can be proven, and why it is always the opposite what we want (Falsification)
    • Interpreting the results of Hypothesis Testing
    • Testing Means
  • Power
    • How to determine a good (and cheap) sample size
    • False positive and false negative and why it is always a trade-off

Declaração de Clientes

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★★★★★

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