Course title

Pre-requisite

Course description

We would like to offer Explorations in Data Science as an alternative to Algebra II or a 4th credit math course.

Explorations in Data Science will prepare students to have a better preparation for advanced courses in statistics as well as to prepare for careers that use data which is becoming more prevalent in our data rich society. Topics will include:

• What are variability; data; and models?
• Data ethics
• Data science inquiry: asking questions of data
• Univariate; bivariate and multivariate data
• Creating visual representations
• What is the story I can tell from this data?
• Data cleaning
• Using measures of center and spread to model data
• Distributions and normal distributions
• Data representations
• Bias
• Data collection and cleaning
• Normalization and weighting of data
• Forming mathematical models
• Sensitivity analysis
• Writing reports and communicating findings
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• Sampling and variability
• Probabilistic thinking
• Linear regression and bivariate data
• Using probability to analyze the fit of a regression
• Make connections between the trend and the context to make predictions
• Spurious correlations; confounding and mediating variables and data ethics
• Evaluating claims: spurious correlation vs causality
  • Algorithmic Thinking
  • Basics of Programming
    • Variables
    • Loops
    • If-then statements
  • Simulation
  • Variability
  • Probability
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• Theoretical and Experimental Probability
• Conditional Probability
• Pros and cons of different ways of data collecting
• Collecting categorical data
• • • Two-way tables
    • Foundations in Linear Algebra: Working in higher dimensional spaces
    • Introduction to clustering
    • • Probability
• Predictive modeling
• Machine learning
• Basic programming
• Linear Algebra
• Conditional Probability

School country

School state

School city

School / district Address

School zip code

Requested competency code

Date submitted

Approved

Approved competency code

• MTH3
• 4 years of Math

Approved date

Online / Virtual