Introduction to Statistics and Understanding Data

Essential Question:

How can we effectively read, understand, and communicate statistical information?

Portrait of a Graduate:

Critical Thinking: Analyze and interpret statistical data to make informed decisions.

Communication: Convey statistical findings clearly through various formats, including visual and written means.

Learner’s Mindset: Show curiosity about data and statistics, continually seeking to improve understanding and skills.

Inquiry Question:

What are the basic concepts and terms used in statistics, such as mean, median, and mode?

2. Inquiry Question:

How can we interpret and analyze data to draw meaningful conclusions?

3. Inquiry Question:

What are the best practices for communicating statistical findings clearly and accurately?

Student Outcomes:

Calculate and interpret measures of central tendency and variability.

2. Student Outcomes:

Analyze real-world data sets to identify trends, patterns, and outliers.

3. Student Outcomes:

Present statistical findings using appropriate charts, graphs, and written explanations.

Skills Demonstrated:

Data Analysis: Ability to calculate and interpret statistical measures, including frequency tables.
Critical Evaluation: Assess the quality and reliability of statistical information.
Effective Communication: Present data and findings in a clear, concise, and accurate manner.
Sampling and Experimental Design: Understand the principles of sampling and design experiments to collect reliable data.

Standards:

CCSS.Math.Content.HSS.ID.A.1: Represent data with plots on the real number line (dot plots, histograms, and box plots).

CCSS.Math.Content.HSS.ID.A.2: Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.

CCSS.Math.Content.HSS.IC.B.6: Evaluate reports based on data.

Resources:

Khan Academy: Lessons on basic statistics and probability.
Statistical Software (e.g., Excel, R): Tools for data analysis and visualization.
Online Data Sets: Access to real-world data for practice and analysis.
Textbooks and Guides: Comprehensive resources on statistical methods and communication.
Research Articles: Examples of experimental design and sampling methods in practice.
Openstax Introductory Statistics

[Our Hidden Google Drive Resource link]

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