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Statistically Speaking - Understanding the fundamentals

Cost: $180 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Recognise the importance of data-driven decision making

  • Understand and interpret different data visualisations

  • Have a basic understanding of inferential statistics methods (i.e. hypothesis testing, correlation and regression)

  • Interpret simple outputs of the above inferential statistics methods

  • Have an awareness of the caveats and nuances in the interpretation of statistical results

 

Outline of Programme:

  • Descriptive Statistics

  • Common Data Visualisations

  • Population vs Sample

  • Confidence Intervals

  • Correlation and Linear Regression

Anchor 1

Making Sense of Data

Cost: $380 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Recognise that there are different types of data related questions and data analytics

  • Apply exploratory and descriptive analysis to glean insights from the data

  • Understand the key principles of effective data visualisation

  • Create short presentations that effectively present the data story

 

Outline of Programme:

  • Knowledge Discovery process

  • Using basic Data Analysis methods using Excel (e.g. Pivot Table/Chart, Data Analysis Toolpak) to distil key insights from a dataset

  • Conceptualising effective Data Visualisations

  • Communicating insights through a data story

Anchor 2

Data Storytelling

Cost: $180 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Recognise the various types of story structures

  • Understand the structure/framework of a good data storyboard

  • Have an awareness of the key principles behind developing a compelling data story

  • Build a simple storyboard using a case study

 

Outline of Programme:

  • Principles of effective Data Visualisations

  • Elements of a data story

  • Story structures (e.g. Freytag’s pyramid, Toulmin’s model)

  • Key principles of a compelling data story

Anchor 3

Significant or not

Cost: $380 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Transform a relevant query and formulate it into a hypothesis

  • Use a gathered data sample to carry out the process of hypothesis testing on means in Excel

  • Interpret the output and make a conclusion about the means

  • Quantify the error of the conclusion and be cognizant of the consideration of practical significance

  • Appreciate the concepts of hypothesis testing and be able to engage in discussions on this topic

 

Outline of Programme:

  • Formulation of hypothesis

  • Concepts of hypothesis testing

  • Testing of mean using Excel

  • Statistical vs practical significance

  • Analysis of variance (ANOVA)

Anchor 4

Data Preparation and Manipulation

Cost: $380 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Understand what is meant by ‘clean’ data and its importance

  • Inspect and clean datasets for analysis purposes

  • Recognise the importance of documentation in the data preparation phase

  • Be able to manipulate data for analytical purposes

 

Outline of Programme:

  • Importance of ‘clean’ data

  • Metadata catalogue

  • Data inspection and cleaning

  • Data manipulation and transformation

Anchor 5

A tale of three regressions

Cost: $380 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Tell when to use single linear regression (SLR), multiple linear regression (MLR) and logistic regression

  • Generate the respective models using Excel

  • Interpret the coefficients and the various statistics

  • Assess the fit of a model and compare across models

  • Use logistic regression to perform classification

  • Understand and appreciate the concept of a model

 

Outline of Programme:

  • Concepts of modelling

  • Simple linear regression

  • Multiple linear regression

  • Logistic regression

Anchor 6

Fundamentals of Machine Learning

Cost: $380 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Understand the big ideas of machine learning (e.g. supervised vs unsupervised machine learning)

  • Recognise the difference between bias and variance

  • Evaluate difference models in terms of metrics

  • Have an awareness of different machine learning techniques and interpret its output

 

Outline of Programme:

  • Supervised vs Unsupervised machine learning

  • Bias and Variance

  • Model evaluation metrics (e.g. accuracy, sensitivity, specificity)

  • K-nearest neighbour

  • K-means clustering

  • Decision Tree

Anchor 7
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