1. Algebra 1 Institute Overview
Summer 2014
4/30/2019
Algebra 1 Institute

2. Overarching Goals
Provide teacher participants with details on how the Algebra 1 curriculum has been reorganized according to the CCSS as it pertains to the development of statistical concepts and elementary notions of probability.
Improve participants’ knowledge of the application of the CCSS mathematical practices in the classroom.
Improve Algebra 1 content-knowledge and model effective instructional strategies that promote student learning in mathematics.
4/30/2019
Algebra 1 Institute

3. Main Topic and Description
Statistical methods explain complex data sets through simple numeric and graphical descriptions and the use of basic mathematical models.
This institute uses statistics and probability to describe natural variability inherent in our surroundings.
4/30/2019
Algebra 1 Institute

4. Institute Structure - 7 units
Data and Variability
Graphical Descriptions of Data
Numerical Descriptions of Data
Bivariate Data
Estimating Probabilities
Sampling and Inference
Modeling Data
Cory, Scotty, Me
4/30/2019
Algebra 1 Institute

5. Big Ideas The process of using statistics
Summarize and represent data: concepts and technology
The determination and meaning of common statistical measures, e.g., mean, median, interquartile range.
The necessity and techniques of random sampling.
4/30/2019
Algebra 1 Institute

6. Unit 1 – Data and Variability
Data collected from observations and experiments is inherently variable. Conclusions drawn from data must take this into account. This unit introduces general categories of data and explains simple methods and terminology needed to describe data.
4/30/2019
Algebra 1 Institute

7. Unit 1 – Essential Questions
What is statistics?
What is a statistical question?
What are some possible errors made doing measurements?
How to recognize bias in the wording of survey questions?
What is simple random sample?
Could bias occur in the sampling process?
Does the sample size have an effect on statistical information?
What are other methods of sampling?
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Algebra 1 Institute

8. Unit 1 – Activities The Question Formulation
Data Measurement and Variation Uncertainty
The Survey Predilection
The Sampling Proclivity
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Algebra 1 Institute

9. Unit 2 – Graphical Description of Data
Participants will learn ways to graphically represent and summarize data.
4/30/2019
Algebra 1 Institute

10. Unit 2 – Essential Questions
How can data be represented graphically?
What are the differences and similarities between boxplots, histograms, and dotplots?
When is more appropriate to use each one of them?
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Algebra 1 Institute

11. Unit 2 – Activities The Categorical Predilection
The Grapevine Fabrication
The Minute Paradigm
The Old Faithful Geyser Prognostication
4/30/2019
Algebra 1 Institute

12. Unit 3 – Numerical Description of Data
Data sets can be summarized by condensing the information down into just a few numeric statistics. The participants will learn ways to numerically represent and summarize data.
4/30/2019
Algebra 1 Institute

13. Unit 3 – Essential Questions
How are the central tendencies of mean and median alike? When is more appropriate to use each one?
How are the interquartile ranges useful when describing data sets?
What is a normal distribution?
What is the probability that a random variable fall in a given interval in a normal distribution?
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Algebra 1 Institute

14. Unit 3 – Activities The Noodle Conundrum The Fair Allocation Paradigm
The Mean and Median Fluctuation
The Migraine Reaction
The Word Memorization Saturation
4/30/2019
Algebra 1 Institute

15. Unit 4 – Bivariate Data
Participants will use graphical and numerical statistical methods to understand the relationship between two sets of data.
4/30/2019
Algebra 1 Institute

16. Unit 4 – Essential Questions
How can distributions from two different sample sets be compared numerically?
How can distributions from two different sample sets be compared graphically?
How can bivariate data be represented in a frequency table?
What does it mean for two data sets to be correlated?
How can the correlation of two data sets be determined numerically?
How can the correlation of two data sets be estimated from a scatterplot?
What is causation?
What is the difference between correlation and causation?
4/30/2019
Algebra 1 Institute

17. Unit 4 – Activities The Height and Arm Span Juxtaposition
The Olympic Quandary
The Outlier Deviation
The Correlation vs. Causation Turmoil
The Table Categorization
The Weather Turbulence
The Patterns Observation
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Algebra 1 Institute

18. Unit 5 – Estimating Probabilities
Participants will study and engage in the estimation and application of probability and random sampling.
4/30/2019
Algebra 1 Institute

19. Unit 5 – Essential Questions
How can one generate a random sample via simulation?
What do the results of a computer random number generator mean?
What does “the probability of tossing a head equals one-half” mean?
4/30/2019
Algebra 1 Institute

20. Unit 5 – Activities The ESP Verification The Fair Unfair Polarization
The Poker Manipulation
The Birthday Paradox
The Stick, Flip, Switch Corollary
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Algebra 1 Institute

21. Unit 6 – Sampling and Inference
Random sampling is useful for making generalizations from a sample to the entire population. This unit describes the properties of random samples, how to generate them, and using simple numeric estimates from samples to infer information about the general population.
4/30/2019
Algebra 1 Institute

22. Unit 6 – Essential Questions
What is a random sample and what do they represent?
How can random samples be generated?
How can random samples be used to predict information regarding a population? How accurate are those predictions?
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Algebra 1 Institute

23. Unit 6 – Activities The Discrimination Fragmentation
The Cholesterol Diet Emanation
The Distribution Normality
The Walking Instability
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Algebra 1 Institute

24. Unit 7 – Modeling Data
This unit explores simple statistical methods for modeling the relation between two sets of data. Linear and exponential models are explored.
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Algebra 1 Institute

25. Unit 7 – Essential Questions
How can the relation between two data sets be modeled?
What is a line of best fit? What does it represent?
What is the effect of rescaling in the line of best fit?
What is the degree of fit for a linear relation? How is the degree of fit related to correlation?
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Algebra 1 Institute

26. Unit 7 – Activities The Starbuck Customer Hypothesis
The Treatment Effect Acquisition
The Soft Drink and Heart Disease Acquisition
4/30/2019
Algebra 1 Institute