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High School Data Analytics and Database Design

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Suggested Prerequisites

Foundations of Programming, Procedural Programming

Description

Did you know that data can tell a story? In this course, you will explore data and databases through the fictional pet services company Critter Sitters. By examining real-world examples, you will learn how data can tell a story and gain the skills to analyze and make decisions from it. You will also expand and apply your Python skills to data science principles, from data dashboards to statistical analysis. Additionally, you will learn about data management, including using and storing quality data and how to spot biases within it. You will uncover how to create a database, write queries, and explore strategies for securing databases. By the end of this course, you will have a foundational understanding of data and databases and the exciting career opportunities available in the data science field.

Module One: Storytelling

-Data science

-Storytelling with data

-Data representations

-Decoding data

-Time series data

-Drawing conclusions and making predictions using data

-Data biases

-Categorizing data

-Using statistics

-Google Colaboratory

-Python packages

-Creating tables with the Pandas package

-Reading csv/Excel files with Pandas

-Data processing cycle

-Types of data

-Collecting and organizing data

-Online datasets

-Interpreting data


Module Two: Visualizing

-Visual cues

-Simple and complex charts

-Shaping data

-Chart types

-Chart elements

-Chart junk

-Planning a presentation

-Designing a presentation

-Considering the audience

-Coding multi-dimensional data

-Strengths and weaknesses of data dashboards

-Cleaning data

-Planning a dashboard

-Slicing and dicing data

-Interactive dashboards

-Arranging dashboards

-Visual noise


Module Three: Analyzing

-Permutations

-Combinations

-Percentiles

-Conditional probabilities

-Probability trees

-Independent and dependent events

-Bayes theorem

-Discrete and continuous probabilities

-Binomial probabilities

-Mean, median, and mode

-Ranges and variances

-Normal distribution

-Z-score

-Skewed data distributions

-Statistical sampling

-Standard error

-Confidence intervals

-Hypothesis testing

-Null and alternative hypotheses

-Type I and Type II errors

-Significance test

-Sampling bias

-Cognitive bias

NCAA-Approved Courses

Our NCAA approved courses are updated often. Please visit the NCAA Eligibility Center and use our school code to see all current eligible courses. The FlexPoint Virtual School NCAA High School code is: 850171 

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