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Module 21
Financial Statistics
This module illuminates how statistics and probability are crucial tools in finance by teaching students how to analyze data from samples, make inferences, and apply these concepts in real-world decisions.
This knowledge is fundamental in navigating the uncertainties of financial markets and in making well-informed savings and investment choices.
Module At A Glance
Grade Levels:
6th - 12th
Est. Length:
2-5 Hours (17 slides)
Activities:
4 Activites
Articles:
3 Articles
Languages:
English & Spanish
Curriculum Fit:
Math, Business, Economics, CTE, Social Studies
Standards Alignment:
CEE National Standards, Jump$tart National Standards & Relevant State Standards
Guiding Questions
- How can statistics help us understand a larger population by examining just a sample of it?
- What makes a sample representative of a population?
- What limitations and risks can sampling introduce?
- How do you use data from a random sample to make inferences about a population?
- What is the difference between correlation and causation?
- What are scatter plots and how do they help us visualize trends in data?
Enduring Understandings
- Statistics provide valuable insights into populations by analyzing representative samples, highlighting the importance of sample selection.
- Random sampling is crucial in statistics as it tends to produce the most representative and unbiased samples, leading to valid generalizations.
- Inferences about population characteristics can be drawn by examining and interpreting data from random samples.
- Correlation is not causation, so be sure to think about underlying data when you’re evaluating relationships.
Module Vocab & Key Topics
Statistics
The science of collecting, analyzing, presenting, and interpreting data.
Population
The entire group that is the subject of a statistical study.
Sample
A subset of the population selected for observation and analysis.
Representative Sample
A sample that accurately reflects the characteristics of the population from which it is drawn.
Random Sampling
A method of selecting a sample from a population where each member has an equal chance of being chosen.
Bias
A systematic error in data collection or analysis that leads to incorrect conclusions.
Inference
The process of drawing conclusions about a population based on data collected from a sample.
Correlation
A statistical measure that describes the extent to which two variables change together, but does not imply causation.
Causation
A relationship between two variables where one variable causes a change in another.
Scatter Plot
A type of graph used in statistics to visually display and compare two variables for a set of data.
Trend Line
A line on a scatter plot, drawn to indicate the general course or tendency of the data points.
Sampling Error
The error is caused by observing a sample instead of the whole population, leading to potential inaccuracies in a sample's results.
Confounding Variable
An outside influence that changes the effect of a dependent and independent variable.
Generalization
Extending the results from a sample to a larger population, making assumptions about a whole group based on a sample.
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