Unit 9 Modeling Data
Represent data using a scatterplot.
Understand the meaning of the correlation coefficient.
Describe the difference between correlation and causation.
In this lesson, we have learned about representing two-variable quantitative data with a scatterplot. We have learned that one of the ways we can judge if a line is a good model for the data is by using the correlation coefficient.
Model data with a linear function.
Use a linear model to analyze data.
In this lesson, we modeled data with linear functions. We estimated our own lines of best fit and found linear regressions using technology. We interpreted the slope and
Interpret data using linear models.
Consider questions and necessary data for further research.
In this lesson, we compared two sets of data to draw conclusions about men’s and women’s incomes. We interpreted the meaning of the correlation coefficients, the slope of the regression line, and intercepts of the regression line. We used the data to make claims and challenged the claims of others.
Understand and interpret residuals.
In this lesson, we learned that a residual shows the difference between the
Clarify differences between residuals and correlation coefficients.
Use precise statistical language to discuss uses of data.
In this lesson, we clarified the meaning of correlation coefficients and residuals and how they relate to regression lines.
Represent data with box plots, dot plots, and histograms.
Analyze data represented in different ways.
In this lesson, we focused on single-variable quantitative data. We compared histograms, dot plots, and box plots to consider what aspects of the data are highlighted in each. We learned to look for the center, the shape, and the spread of the data.
Understand standard deviation.
In this lesson, we learned about standard deviation, a measure of spread for single-variable quantitative data. The standard deviation is
Compare sets of data using center, spread, and shape.
In this lesson, we compared data distributions using shape, center, and spread. We learned to consider the interquartile range and the median when using a box plot and to consider the mean and the standard deviation when using a histogram. We also discussed the effect of outliers on the median, mean, and standard deviation.