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Alg1.3 Two-variable Statistics

I can calculate missing values in a two-way table.
I can create a two-way table for categorical data given information in everyday language.
I can describe what the values in a two-way table mean in everyday language.

I can calculate values in a relative frequency table and describe what the values mean in everyday language.

I can look for patterns in two-way tables and relative frequency tables to see if there is a possible association between two variables.

I can describe the rate of change and $y$-intercept for a linear model in everyday language.
I can draw a linear model that fits the data well and use the linear model to estimate values I want to find.

I can describe the rate of change and $y$-intercept for a linear model in everyday language.
I can use technology to find the line of best fit.

I can plot and calculate residuals for a data set and use the information to judge whether a linear model is a good fit.

I can describe the goodness of fit of a linear model using the correlation coefficient.
I can match the correlation coefficient with a scatter plot and linear model.

I can describe the strength of a relationship between two variables.
I can use technology to find the correlation coefficient and explain what the value tells me about a linear model in everyday language.

I can look for connections between two variables to analyze whether or not there is a causal relationship.

I can collect data, create a linear model to fit the data, determine if the linear model is a good fit, and use the information from my linear model to answer questions.