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(Alg 1) Data Analysis and Displays {Bundle} in a PowerPoint Presentation

(Alg 1) Data Analysis and Displays {Bundle} in a PowerPoint Presentation
(Alg 1) Data Analysis and Displays {Bundle} in a PowerPoint Presentation
(Alg 1) Data Analysis and Displays {Bundle} in a PowerPoint Presentation
(Alg 1) Data Analysis and Displays {Bundle} in a PowerPoint Presentation
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Common Core Standards
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Algebra 1 Data Analysis and Displays {Bundle} in a PowerPoint Presentation

This is a bundle include the eight PowerPoint lessons below and two Quiz Show games, Jeopardy Style, for review.

Measures of Central Tendency S.ID.2, S.ID.3
Measures of Dispersion (Standard Deviation) S.ID.2, S.ID.3
Box-and-Whisker Plots S.ID.1, S.ID.2, S.ID.3
Shapes of Distributions S.ID.2, S.ID.3
Quiz Show Game Central Tendencies and Dispersion S.ID.1, S.ID.2, S.ID.3
Scatter Plots and Lines of Fit 8.SP.1, S.ID.6a, S.ID.6c, S.ID.7
Analyzing Lines of Fit S.ID.6b, S.ID.7, S.ID.8, S.ID.9
Two-Way Tables 8.SP.4, S.ID.5
Choosing a Data Display S.ID.1
Quiz Show Game Tables and Displays 8.SP.1, 8.SP.4, S.ID.1, S.ID.5, S.ID.6a, S.ID.6b, S.ID.6c, S.ID.7, S.ID.8, S.ID.9

Students often get lost in multi-step math problems. This PowerPoint lesson is unique because it uses a flow-through technique, guided animation, that helps to eliminate confusion and guides the student through the problem. The lesson highlights each step of the problem as the teacher is discussing it, and then animates it to the next step within the lesson. Every step of every problem is shown, even the minor or seemingly insignificant steps. A helpful color-coding technique engages the students and guides them through the problem (Green is for the answer, red for wrong or canceled numbers, & blue, purple & sometimes orange for focusing the next step or separating things.) Twice as many examples are provided, compared to a standard textbook. All lessons have a real-world example to aid the students in visualizing a practical application of the concept.

This lesson applies to the Common Core Standard:
Statistics & Probability 8.SP.1, 8.SP.4
Investigate patterns of association in bivariate data.
1. Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.

4. Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?

High School: Statistics & Probability » Interpreting Categorical & Quantitative Data S.ID.1, S.ID.2, S.ID.3, S.ID.4, S.ID.5, S.ID.6a, S.ID.6b, S.ID.6c, S.ID.7, S.ID.8, S.ID.9
Summarize, represent, and interpret data on a single count or measurement variable
1. Represent data with plots on the real number line (dot plots, histograms, and box plots).

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.

3. Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

4. Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.

Summarize, represent, and interpret data on two categorical and quantitative variables
5. Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.

6. Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
a. Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.

b. Informally assess the fit of a function by plotting and analyzing residuals.

c. Fit a linear function for a scatter plot that suggests a linear association.

Interpret linear models
7. Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

8. Compute (using technology) and interpret the correlation coefficient of a linear fit.

9. Distinguish between correlation and causation.

Please note that these PowerPoints are not editable.

If you need an alternative version because your country uses different measurements, units, slight wording adjustment for language differences, or a slide reordering just ask.

Are you looking for the Algebra 1 Curriculum Bundle? Click here!

This resource is for one teacher only. You may not upload this resource to the internet in any form. Additional teachers must purchase their own license. If you are a coach, principal or district interested in purchasing several licenses, please contact me for a district-wide quote at prestonpowerpoints@gmail.com. This product may not be uploaded to the internet in any form, including classroom/personal websites or network drives.
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